--- _id: '12467' abstract: - lang: eng text: Safety and liveness are elementary concepts of computation, and the foundation of many verification paradigms. The safety-liveness classification of boolean properties characterizes whether a given property can be falsified by observing a finite prefix of an infinite computation trace (always for safety, never for liveness). In quantitative specification and verification, properties assign not truth values, but quantitative values to infinite traces (e.g., a cost, or the distance to a boolean property). We introduce quantitative safety and liveness, and we prove that our definitions induce conservative quantitative generalizations of both (1)~the safety-progress hierarchy of boolean properties and (2)~the safety-liveness decomposition of boolean properties. In particular, we show that every quantitative property can be written as the pointwise minimum of a quantitative safety property and a quantitative liveness property. Consequently, like boolean properties, also quantitative properties can be min-decomposed into safety and liveness parts, or alternatively, max-decomposed into co-safety and co-liveness parts. Moreover, quantitative properties can be approximated naturally. We prove that every quantitative property that has both safe and co-safe approximations can be monitored arbitrarily precisely by a monitor that uses only a finite number of states. acknowledgement: We thank the anonymous reviewers for their helpful comments. This work was supported in part by the ERC-2020-AdG 101020093. alternative_title: - LNCS article_processing_charge: No author: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Nicolas Adrien full_name: Mazzocchi, Nicolas Adrien id: b26baa86-3308-11ec-87b0-8990f34baa85 last_name: Mazzocchi - first_name: Naci E full_name: Sarac, Naci E id: 8C6B42F8-C8E6-11E9-A03A-F2DCE5697425 last_name: Sarac citation: ama: 'Henzinger TA, Mazzocchi NA, Sarac NE. Quantitative safety and liveness. In: 26th International Conference Foundations of Software Science and Computation Structures. Vol 13992. Springer Nature; 2023:349-370. doi:10.1007/978-3-031-30829-1_17' apa: 'Henzinger, T. A., Mazzocchi, N. A., & Sarac, N. E. (2023). Quantitative safety and liveness. In 26th International Conference Foundations of Software Science and Computation Structures (Vol. 13992, pp. 349–370). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-30829-1_17' chicago: Henzinger, Thomas A, Nicolas Adrien Mazzocchi, and Naci E Sarac. “Quantitative Safety and Liveness.” In 26th International Conference Foundations of Software Science and Computation Structures, 13992:349–70. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30829-1_17. ieee: T. A. Henzinger, N. A. Mazzocchi, and N. E. Sarac, “Quantitative safety and liveness,” in 26th International Conference Foundations of Software Science and Computation Structures, Paris, France, 2023, vol. 13992, pp. 349–370. ista: 'Henzinger TA, Mazzocchi NA, Sarac NE. 2023. Quantitative safety and liveness. 26th International Conference Foundations of Software Science and Computation Structures. FOSSACS: Foundations of Software Science and Computation Structures, LNCS, vol. 13992, 349–370.' mla: Henzinger, Thomas A., et al. “Quantitative Safety and Liveness.” 26th International Conference Foundations of Software Science and Computation Structures, vol. 13992, Springer Nature, 2023, pp. 349–70, doi:10.1007/978-3-031-30829-1_17. short: T.A. Henzinger, N.A. Mazzocchi, N.E. Sarac, in:, 26th International Conference Foundations of Software Science and Computation Structures, Springer Nature, 2023, pp. 349–370. conference: end_date: 2023-04-27 location: Paris, France name: 'FOSSACS: Foundations of Software Science and Computation Structures' start_date: 2023-04-22 date_created: 2023-01-31T07:23:56Z date_published: 2023-04-21T00:00:00Z date_updated: 2023-07-14T11:20:27Z day: '21' ddc: - '000' department: - _id: GradSch - _id: ToHe doi: 10.1007/978-3-031-30829-1_17 ec_funded: 1 external_id: arxiv: - '2301.11175' file: - access_level: open_access checksum: 981025aed580b6b27c426cb8856cf63e content_type: application/pdf creator: esarac date_created: 2023-01-31T07:22:21Z date_updated: 2023-01-31T07:22:21Z file_id: '12468' file_name: qsl.pdf file_size: 449027 relation: main_file success: 1 - access_level: open_access checksum: f16e2af1e0eb243158ab0f0fe74e7d5a content_type: application/pdf creator: dernst date_created: 2023-06-19T10:28:09Z date_updated: 2023-06-19T10:28:09Z file_id: '13153' file_name: 2023_LNCS_HenzingerT.pdf file_size: 1048171 relation: main_file success: 1 file_date_updated: 2023-06-19T10:28:09Z has_accepted_license: '1' intvolume: ' 13992' language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '04' oa: 1 oa_version: Published Version page: 349-370 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 26th International Conference Foundations of Software Science and Computation Structures publication_identifier: eissn: - 1611-3349 isbn: - '9783031308284' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Quantitative safety and liveness tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 volume: 13992 year: '2023' ... --- _id: '13292' abstract: - lang: eng text: The operator precedence languages (OPLs) represent the largest known subclass of the context-free languages which enjoys all desirable closure and decidability properties. This includes the decidability of language inclusion, which is the ultimate verification problem. Operator precedence grammars, automata, and logics have been investigated and used, for example, to verify programs with arithmetic expressions and exceptions (both of which are deterministic pushdown but lie outside the scope of the visibly pushdown languages). In this paper, we complete the picture and give, for the first time, an algebraic characterization of the class of OPLs in the form of a syntactic congruence that has finitely many equivalence classes exactly for the operator precedence languages. This is a generalization of the celebrated Myhill-Nerode theorem for the regular languages to OPLs. As one of the consequences, we show that universality and language inclusion for nondeterministic operator precedence automata can be solved by an antichain algorithm. Antichain algorithms avoid determinization and complementation through an explicit subset construction, by leveraging a quasi-order on words, which allows the pruning of the search space for counterexample words without sacrificing completeness. Antichain algorithms can be implemented symbolically, and these implementations are today the best-performing algorithms in practice for the inclusion of finite automata. We give a generic construction of the quasi-order needed for antichain algorithms from a finite syntactic congruence. This yields the first antichain algorithm for OPLs, an algorithm that solves the ExpTime-hard language inclusion problem for OPLs in exponential time. acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093.\r\nWe thank Pierre Ganty for early discussions and the anonymous reviewers for their helpful comments.\r\n" alternative_title: - LIPIcs article_processing_charge: Yes author: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Pavol full_name: Kebis, Pavol last_name: Kebis - first_name: Nicolas Adrien full_name: Mazzocchi, Nicolas Adrien id: b26baa86-3308-11ec-87b0-8990f34baa85 last_name: Mazzocchi - first_name: Naci E full_name: Sarac, Naci E id: 8C6B42F8-C8E6-11E9-A03A-F2DCE5697425 last_name: Sarac citation: ama: 'Henzinger TA, Kebis P, Mazzocchi NA, Sarac NE. Regular methods for operator precedence languages. In: 50th International Colloquium on Automata, Languages, and Programming. Vol 261. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2023:129:1--129:20. doi:10.4230/LIPIcs.ICALP.2023.129' apa: 'Henzinger, T. A., Kebis, P., Mazzocchi, N. A., & Sarac, N. E. (2023). Regular methods for operator precedence languages. In 50th International Colloquium on Automata, Languages, and Programming (Vol. 261, p. 129:1--129:20). Paderborn, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.ICALP.2023.129' chicago: Henzinger, Thomas A, Pavol Kebis, Nicolas Adrien Mazzocchi, and Naci E Sarac. “Regular Methods for Operator Precedence Languages.” In 50th International Colloquium on Automata, Languages, and Programming, 261:129:1--129:20. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023. https://doi.org/10.4230/LIPIcs.ICALP.2023.129. ieee: T. A. Henzinger, P. Kebis, N. A. Mazzocchi, and N. E. Sarac, “Regular methods for operator precedence languages,” in 50th International Colloquium on Automata, Languages, and Programming, Paderborn, Germany, 2023, vol. 261, p. 129:1--129:20. ista: 'Henzinger TA, Kebis P, Mazzocchi NA, Sarac NE. 2023. Regular methods for operator precedence languages. 50th International Colloquium on Automata, Languages, and Programming. ICALP: International Colloquium on Automata, Languages, and Programming, LIPIcs, vol. 261, 129:1--129:20.' mla: Henzinger, Thomas A., et al. “Regular Methods for Operator Precedence Languages.” 50th International Colloquium on Automata, Languages, and Programming, vol. 261, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023, p. 129:1--129:20, doi:10.4230/LIPIcs.ICALP.2023.129. short: T.A. Henzinger, P. Kebis, N.A. Mazzocchi, N.E. Sarac, in:, 50th International Colloquium on Automata, Languages, and Programming, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023, p. 129:1--129:20. conference: end_date: 2023-07-14 location: Paderborn, Germany name: 'ICALP: International Colloquium on Automata, Languages, and Programming' start_date: 2023-07-10 date_created: 2023-07-24T15:11:41Z date_published: 2023-07-05T00:00:00Z date_updated: 2023-07-31T08:38:38Z day: '05' ddc: - '000' department: - _id: GradSch - _id: ToHe doi: 10.4230/LIPIcs.ICALP.2023.129 ec_funded: 1 external_id: arxiv: - '2305.03447' file: - access_level: open_access checksum: 5d4c8932ef3450615a53b9bb15d92eb2 content_type: application/pdf creator: esarac date_created: 2023-07-24T15:11:05Z date_updated: 2023-07-24T15:11:05Z file_id: '13293' file_name: icalp23.pdf file_size: 859379 relation: main_file success: 1 file_date_updated: 2023-07-24T15:11:05Z has_accepted_license: '1' intvolume: ' 261' language: - iso: eng month: '07' oa: 1 oa_version: Published Version page: 129:1--129:20 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 50th International Colloquium on Automata, Languages, and Programming publication_identifier: eissn: - 1868-8969 isbn: - '9783959772785' publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' status: public title: Regular methods for operator precedence languages tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 261 year: '2023' ... --- _id: '12704' abstract: - lang: eng text: Adversarial training (i.e., training on adversarially perturbed input data) is a well-studied method for making neural networks robust to potential adversarial attacks during inference. However, the improved robustness does not come for free but rather is accompanied by a decrease in overall model accuracy and performance. Recent work has shown that, in practical robot learning applications, the effects of adversarial training do not pose a fair trade-off but inflict a net loss when measured in holistic robot performance. This work revisits the robustness-accuracy trade-off in robot learning by systematically analyzing if recent advances in robust training methods and theory in conjunction with adversarial robot learning, are capable of making adversarial training suitable for real-world robot applications. We evaluate three different robot learning tasks ranging from autonomous driving in a high-fidelity environment amenable to sim-to-real deployment to mobile robot navigation and gesture recognition. Our results demonstrate that, while these techniques make incremental improvements on the trade-off on a relative scale, the negative impact on the nominal accuracy caused by adversarial training still outweighs the improved robustness by an order of magnitude. We conclude that although progress is happening, further advances in robust learning methods are necessary before they can benefit robot learning tasks in practice. acknowledgement: "We thank Christoph Lampert for inspiring this work. The\r\nviews and conclusions contained in this document are those of\r\nthe authors and should not be interpreted as representing the\r\nofficial policies, either expressed or implied, of the United States\r\nAir Force or the U.S. Government. The U.S. Government is\r\nauthorized to reproduce and distribute reprints for Government\r\npurposes notwithstanding any copyright notation herein." article_processing_charge: No article_type: original author: - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Alexander full_name: Amini, Alexander last_name: Amini - first_name: Daniela full_name: Rus, Daniela last_name: Rus - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: Lechner M, Amini A, Rus D, Henzinger TA. Revisiting the adversarial robustness-accuracy tradeoff in robot learning. IEEE Robotics and Automation Letters. 2023;8(3):1595-1602. doi:10.1109/LRA.2023.3240930 apa: Lechner, M., Amini, A., Rus, D., & Henzinger, T. A. (2023). Revisiting the adversarial robustness-accuracy tradeoff in robot learning. IEEE Robotics and Automation Letters. Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/LRA.2023.3240930 chicago: Lechner, Mathias, Alexander Amini, Daniela Rus, and Thomas A Henzinger. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” IEEE Robotics and Automation Letters. Institute of Electrical and Electronics Engineers, 2023. https://doi.org/10.1109/LRA.2023.3240930. ieee: M. Lechner, A. Amini, D. Rus, and T. A. Henzinger, “Revisiting the adversarial robustness-accuracy tradeoff in robot learning,” IEEE Robotics and Automation Letters, vol. 8, no. 3. Institute of Electrical and Electronics Engineers, pp. 1595–1602, 2023. ista: Lechner M, Amini A, Rus D, Henzinger TA. 2023. Revisiting the adversarial robustness-accuracy tradeoff in robot learning. IEEE Robotics and Automation Letters. 8(3), 1595–1602. mla: Lechner, Mathias, et al. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” IEEE Robotics and Automation Letters, vol. 8, no. 3, Institute of Electrical and Electronics Engineers, 2023, pp. 1595–602, doi:10.1109/LRA.2023.3240930. short: M. Lechner, A. Amini, D. Rus, T.A. Henzinger, IEEE Robotics and Automation Letters 8 (2023) 1595–1602. date_created: 2023-03-05T23:01:04Z date_published: 2023-03-01T00:00:00Z date_updated: 2023-08-01T13:36:50Z day: '01' ddc: - '000' department: - _id: ToHe doi: 10.1109/LRA.2023.3240930 external_id: arxiv: - '2204.07373' isi: - '000936534100012' file: - access_level: open_access checksum: 5a75dcd326ea66685de2b1aaec259e85 content_type: application/pdf creator: cchlebak date_created: 2023-03-07T12:22:23Z date_updated: 2023-03-07T12:22:23Z file_id: '12714' file_name: 2023_IEEERobAutLetters_Lechner.pdf file_size: 944052 relation: main_file success: 1 file_date_updated: 2023-03-07T12:22:23Z has_accepted_license: '1' intvolume: ' 8' isi: 1 issue: '3' language: - iso: eng month: '03' oa: 1 oa_version: Published Version page: 1595-1602 publication: IEEE Robotics and Automation Letters publication_identifier: eissn: - 2377-3766 publication_status: published publisher: Institute of Electrical and Electronics Engineers quality_controlled: '1' related_material: record: - id: '11366' relation: earlier_version status: public scopus_import: '1' status: public title: Revisiting the adversarial robustness-accuracy tradeoff in robot learning tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 8 year: '2023' ... --- _id: '12876' abstract: - lang: eng text: "Motivation: The problem of model inference is of fundamental importance to systems biology. Logical models (e.g. Boolean networks; BNs) represent a computationally attractive approach capable of handling large biological networks. The models are typically inferred from experimental data. However, even with a substantial amount of experimental data supported by some prior knowledge, existing inference methods often focus on a small sample of admissible candidate models only.\r\n\r\nResults: We propose Boolean network sketches as a new formal instrument for the inference of Boolean networks. A sketch integrates (typically partial) knowledge about the network’s topology and the update logic (obtained through, e.g. a biological knowledge base or a literature search), as well as further assumptions about the properties of the network’s transitions (e.g. the form of its attractor landscape), and additional restrictions on the model dynamics given by the measured experimental data. Our new BNs inference algorithm starts with an ‘initial’ sketch, which is extended by adding restrictions representing experimental data to a ‘data-informed’ sketch and subsequently computes all BNs consistent with the data-informed sketch. Our algorithm is based on a symbolic representation and coloured model-checking. Our approach is unique in its ability to cover a broad spectrum of knowledge and efficiently produce a compact representation of all inferred BNs. We evaluate the method on a non-trivial collection of real-world and simulated data." acknowledgement: This work was partially supported by GACR [grant No. GA22-10845S]; and Grant Agency of Masaryk University [grant No. MUNI/G/1771/2020]. This work was partially supported by European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie [Grant Agreement No. 101034413 to S.P.]. article_number: btad158 article_processing_charge: No article_type: original author: - first_name: Nikola full_name: Beneš, Nikola last_name: Beneš - first_name: Luboš full_name: Brim, Luboš last_name: Brim - first_name: Ondřej full_name: Huvar, Ondřej last_name: Huvar - first_name: Samuel full_name: Pastva, Samuel id: 07c5ea74-f61c-11ec-a664-aa7c5d957b2b last_name: Pastva - first_name: David full_name: Šafránek, David last_name: Šafránek citation: ama: 'Beneš N, Brim L, Huvar O, Pastva S, Šafránek D. Boolean network sketches: A unifying framework for logical model inference. Bioinformatics. 2023;39(4). doi:10.1093/bioinformatics/btad158' apa: 'Beneš, N., Brim, L., Huvar, O., Pastva, S., & Šafránek, D. (2023). Boolean network sketches: A unifying framework for logical model inference. Bioinformatics. Oxford Academic. https://doi.org/10.1093/bioinformatics/btad158' chicago: 'Beneš, Nikola, Luboš Brim, Ondřej Huvar, Samuel Pastva, and David Šafránek. “Boolean Network Sketches: A Unifying Framework for Logical Model Inference.” Bioinformatics. Oxford Academic, 2023. https://doi.org/10.1093/bioinformatics/btad158.' ieee: 'N. Beneš, L. Brim, O. Huvar, S. Pastva, and D. Šafránek, “Boolean network sketches: A unifying framework for logical model inference,” Bioinformatics, vol. 39, no. 4. Oxford Academic, 2023.' ista: 'Beneš N, Brim L, Huvar O, Pastva S, Šafránek D. 2023. Boolean network sketches: A unifying framework for logical model inference. Bioinformatics. 39(4), btad158.' mla: 'Beneš, Nikola, et al. “Boolean Network Sketches: A Unifying Framework for Logical Model Inference.” Bioinformatics, vol. 39, no. 4, btad158, Oxford Academic, 2023, doi:10.1093/bioinformatics/btad158.' short: N. Beneš, L. Brim, O. Huvar, S. Pastva, D. Šafránek, Bioinformatics 39 (2023). date_created: 2023-04-30T22:01:05Z date_published: 2023-04-03T00:00:00Z date_updated: 2023-08-01T14:27:28Z day: '03' ddc: - '000' department: - _id: ToHe doi: 10.1093/bioinformatics/btad158 ec_funded: 1 external_id: isi: - '000976610800001' pmid: - '37004199' file: - access_level: open_access checksum: 2cb90ddf781baefddf47eac4b54e2a03 content_type: application/pdf creator: dernst date_created: 2023-05-02T07:39:04Z date_updated: 2023-05-02T07:39:04Z file_id: '12886' file_name: 2023_Bioinformatics_Benes.pdf file_size: 478740 relation: main_file success: 1 file_date_updated: 2023-05-02T07:39:04Z has_accepted_license: '1' intvolume: ' 39' isi: 1 issue: '4' language: - iso: eng month: '04' oa: 1 oa_version: Published Version pmid: 1 project: - _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c call_identifier: H2020 grant_number: '101034413' name: 'IST-BRIDGE: International postdoctoral program' publication: Bioinformatics publication_identifier: eissn: - 1367-4811 publication_status: published publisher: Oxford Academic quality_controlled: '1' related_material: link: - relation: software url: https://doi.org/10.5281/zenodo.7688740 scopus_import: '1' status: public title: 'Boolean network sketches: A unifying framework for logical model inference' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 39 year: '2023' ... --- _id: '14242' abstract: - lang: eng text: We study the problem of training and certifying adversarially robust quantized neural networks (QNNs). Quantization is a technique for making neural networks more efficient by running them using low-bit integer arithmetic and is therefore commonly adopted in industry. Recent work has shown that floating-point neural networks that have been verified to be robust can become vulnerable to adversarial attacks after quantization, and certification of the quantized representation is necessary to guarantee robustness. In this work, we present quantization-aware interval bound propagation (QA-IBP), a novel method for training robust QNNs. Inspired by advances in robust learning of non-quantized networks, our training algorithm computes the gradient of an abstract representation of the actual network. Unlike existing approaches, our method can handle the discrete semantics of QNNs. Based on QA-IBP, we also develop a complete verification procedure for verifying the adversarial robustness of QNNs, which is guaranteed to terminate and produce a correct answer. Compared to existing approaches, the key advantage of our verification procedure is that it runs entirely on GPU or other accelerator devices. We demonstrate experimentally that our approach significantly outperforms existing methods and establish the new state-of-the-art for training and certifying the robustness of QNNs. acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093, ERC CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. Research was sponsored by the United\r\nStates Air Force Research Laboratory and the United States Air Force Artificial Intelligence Accelerator and was accomplished under Cooperative Agreement Number FA8750-19-2-\r\n1000. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied,\r\nof the United States Air Force or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright\r\nnotation herein. The research was also funded in part by the AI2050 program at Schmidt Futures (Grant G-22-63172) and Capgemini SE." article_processing_charge: No author: - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Daniela full_name: Rus, Daniela last_name: Rus citation: ama: 'Lechner M, Zikelic D, Chatterjee K, Henzinger TA, Rus D. Quantization-aware interval bound propagation for training certifiably robust quantized neural networks. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence. Vol 37. Association for the Advancement of Artificial Intelligence; 2023:14964-14973. doi:10.1609/aaai.v37i12.26747' apa: 'Lechner, M., Zikelic, D., Chatterjee, K., Henzinger, T. A., & Rus, D. (2023). Quantization-aware interval bound propagation for training certifiably robust quantized neural networks. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (Vol. 37, pp. 14964–14973). Washington, DC, United States: Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v37i12.26747' chicago: Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, Thomas A Henzinger, and Daniela Rus. “Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks.” In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 37:14964–73. Association for the Advancement of Artificial Intelligence, 2023. https://doi.org/10.1609/aaai.v37i12.26747. ieee: M. Lechner, D. Zikelic, K. Chatterjee, T. A. Henzinger, and D. Rus, “Quantization-aware interval bound propagation for training certifiably robust quantized neural networks,” in Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, DC, United States, 2023, vol. 37, no. 12, pp. 14964–14973. ista: 'Lechner M, Zikelic D, Chatterjee K, Henzinger TA, Rus D. 2023. Quantization-aware interval bound propagation for training certifiably robust quantized neural networks. Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial Intelligence vol. 37, 14964–14973.' mla: Lechner, Mathias, et al. “Quantization-Aware Interval Bound Propagation for Training Certifiably Robust Quantized Neural Networks.” Proceedings of the 37th AAAI Conference on Artificial Intelligence, vol. 37, no. 12, Association for the Advancement of Artificial Intelligence, 2023, pp. 14964–73, doi:10.1609/aaai.v37i12.26747. short: M. Lechner, D. Zikelic, K. Chatterjee, T.A. Henzinger, D. Rus, in:, Proceedings of the 37th AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, 2023, pp. 14964–14973. conference: end_date: 2023-02-14 location: Washington, DC, United States name: 'AAAI: Conference on Artificial Intelligence' start_date: 2023-02-07 date_created: 2023-08-27T22:01:17Z date_published: 2023-06-26T00:00:00Z date_updated: 2023-09-05T07:06:14Z day: '26' department: - _id: ToHe - _id: KrCh doi: 10.1609/aaai.v37i12.26747 ec_funded: 1 external_id: arxiv: - '2211.16187' intvolume: ' 37' issue: '12' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2211.16187 month: '06' oa: 1 oa_version: Preprint page: 14964-14973 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: Proceedings of the 37th AAAI Conference on Artificial Intelligence publication_identifier: isbn: - '9781577358800' publication_status: published publisher: Association for the Advancement of Artificial Intelligence quality_controlled: '1' scopus_import: '1' status: public title: Quantization-aware interval bound propagation for training certifiably robust quantized neural networks type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 37 year: '2023' ... --- _id: '14243' abstract: - lang: eng text: 'Two-player zero-sum "graph games" are central in logic, verification, and multi-agent systems. The game proceeds by placing a token on a vertex of a graph, and allowing the players to move it to produce an infinite path, which determines the winner or payoff of the game. Traditionally, the players alternate turns in moving the token. In "bidding games", however, the players have budgets and in each turn, an auction (bidding) determines which player moves the token. So far, bidding games have only been studied as full-information games. In this work we initiate the study of partial-information bidding games: we study bidding games in which a player''s initial budget is drawn from a known probability distribution. We show that while for some bidding mechanisms and objectives, it is straightforward to adapt the results from the full-information setting to the partial-information setting, for others, the analysis is significantly more challenging, requires new techniques, and gives rise to interesting results. Specifically, we study games with "mean-payoff" objectives in combination with "poorman" bidding. We construct optimal strategies for a partially-informed player who plays against a fully-informed adversary. We show that, somewhat surprisingly, the "value" under pure strategies does not necessarily exist in such games.' acknowledgement: This research was supported in part by ISF grant no.1679/21, by the ERC CoG 863818 (ForM-SMArt), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. article_processing_charge: No author: - first_name: Guy full_name: Avni, Guy id: 463C8BC2-F248-11E8-B48F-1D18A9856A87 last_name: Avni orcid: 0000-0001-5588-8287 - first_name: Ismael R full_name: Jecker, Ismael R id: 85D7C63E-7D5D-11E9-9C0F-98C4E5697425 last_name: Jecker - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 citation: ama: 'Avni G, Jecker IR, Zikelic D. Bidding graph games with partially-observable budgets. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence. Vol 37. ; 2023:5464-5471. doi:10.1609/aaai.v37i5.25679' apa: Avni, G., Jecker, I. R., & Zikelic, D. (2023). Bidding graph games with partially-observable budgets. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (Vol. 37, pp. 5464–5471). Washington, DC, United States. https://doi.org/10.1609/aaai.v37i5.25679 chicago: Avni, Guy, Ismael R Jecker, and Dorde Zikelic. “Bidding Graph Games with Partially-Observable Budgets.” In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 37:5464–71, 2023. https://doi.org/10.1609/aaai.v37i5.25679. ieee: G. Avni, I. R. Jecker, and D. Zikelic, “Bidding graph games with partially-observable budgets,” in Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, DC, United States, 2023, vol. 37, no. 5, pp. 5464–5471. ista: 'Avni G, Jecker IR, Zikelic D. 2023. Bidding graph games with partially-observable budgets. Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial Intelligence vol. 37, 5464–5471.' mla: Avni, Guy, et al. “Bidding Graph Games with Partially-Observable Budgets.” Proceedings of the 37th AAAI Conference on Artificial Intelligence, vol. 37, no. 5, 2023, pp. 5464–71, doi:10.1609/aaai.v37i5.25679. short: G. Avni, I.R. Jecker, D. Zikelic, in:, Proceedings of the 37th AAAI Conference on Artificial Intelligence, 2023, pp. 5464–5471. conference: end_date: 2023-02-14 location: Washington, DC, United States name: 'AAAI: Conference on Artificial Intelligence' start_date: 2023-02-07 date_created: 2023-08-27T22:01:18Z date_published: 2023-06-27T00:00:00Z date_updated: 2023-09-05T08:37:00Z day: '27' department: - _id: ToHe - _id: KrCh doi: 10.1609/aaai.v37i5.25679 ec_funded: 1 external_id: arxiv: - '2211.13626' intvolume: ' 37' issue: '5' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1609/aaai.v37i5.25679 month: '06' oa: 1 oa_version: Published Version page: 5464-5471 project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: Proceedings of the 37th AAAI Conference on Artificial Intelligence publication_identifier: isbn: - '9781577358800' publication_status: published quality_controlled: '1' scopus_import: '1' status: public title: Bidding graph games with partially-observable budgets type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 37 year: '2023' ... --- _id: '13310' abstract: - lang: eng text: Machine-learned systems are in widespread use for making decisions about humans, and it is important that they are fair, i.e., not biased against individuals based on sensitive attributes. We present runtime verification of algorithmic fairness for systems whose models are unknown, but are assumed to have a Markov chain structure. We introduce a specification language that can model many common algorithmic fairness properties, such as demographic parity, equal opportunity, and social burden. We build monitors that observe a long sequence of events as generated by a given system, and output, after each observation, a quantitative estimate of how fair or biased the system was on that run until that point in time. The estimate is proven to be correct modulo a variable error bound and a given confidence level, where the error bound gets tighter as the observed sequence gets longer. Our monitors are of two types, and use, respectively, frequentist and Bayesian statistical inference techniques. While the frequentist monitors compute estimates that are objectively correct with respect to the ground truth, the Bayesian monitors compute estimates that are correct subject to a given prior belief about the system’s model. Using a prototype implementation, we show how we can monitor if a bank is fair in giving loans to applicants from different social backgrounds, and if a college is fair in admitting students while maintaining a reasonable financial burden on the society. Although they exhibit different theoretical complexities in certain cases, in our experiments, both frequentist and Bayesian monitors took less than a millisecond to update their verdicts after each observation. acknowledgement: 'This work is supported by the European Research Council under Grant No.: ERC-2020-AdG101020093.' alternative_title: - LNCS article_processing_charge: Yes (in subscription journal) author: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Mahyar full_name: Karimi, Mahyar id: f1dedef5-2f78-11ee-989a-c4c97bccf506 last_name: Karimi orcid: 0009-0005-0820-1696 - first_name: Konstantin full_name: Kueffner, Konstantin id: 8121a2d0-dc85-11ea-9058-af578f3b4515 last_name: Kueffner orcid: 0000-0001-8974-2542 - first_name: Kaushik full_name: Mallik, Kaushik id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598 last_name: Mallik orcid: 0000-0001-9864-7475 citation: ama: 'Henzinger TA, Karimi M, Kueffner K, Mallik K. Monitoring algorithmic fairness. In: Computer Aided Verification. Vol 13965. Springer Nature; 2023:358–382. doi:10.1007/978-3-031-37703-7_17' apa: 'Henzinger, T. A., Karimi, M., Kueffner, K., & Mallik, K. (2023). Monitoring algorithmic fairness. In Computer Aided Verification (Vol. 13965, pp. 358–382). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-37703-7_17' chicago: Henzinger, Thomas A, Mahyar Karimi, Konstantin Kueffner, and Kaushik Mallik. “Monitoring Algorithmic Fairness.” In Computer Aided Verification, 13965:358–382. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-37703-7_17. ieee: T. A. Henzinger, M. Karimi, K. Kueffner, and K. Mallik, “Monitoring algorithmic fairness,” in Computer Aided Verification, Paris, France, 2023, vol. 13965, pp. 358–382. ista: 'Henzinger TA, Karimi M, Kueffner K, Mallik K. 2023. Monitoring algorithmic fairness. Computer Aided Verification. CAV: Computer Aided Verification, LNCS, vol. 13965, 358–382.' mla: Henzinger, Thomas A., et al. “Monitoring Algorithmic Fairness.” Computer Aided Verification, vol. 13965, Springer Nature, 2023, pp. 358–382, doi:10.1007/978-3-031-37703-7_17. short: T.A. Henzinger, M. Karimi, K. Kueffner, K. Mallik, in:, Computer Aided Verification, Springer Nature, 2023, pp. 358–382. conference: end_date: 2023-07-22 location: Paris, France name: 'CAV: Computer Aided Verification' start_date: 2023-07-17 date_created: 2023-07-25T18:32:40Z date_published: 2023-07-18T00:00:00Z date_updated: 2023-09-05T15:14:00Z day: '18' ddc: - '000' department: - _id: GradSch - _id: ToHe doi: 10.1007/978-3-031-37703-7_17 ec_funded: 1 external_id: arxiv: - '2305.15979' file: - access_level: open_access checksum: ccaf94bf7d658ba012c016e11869b54c content_type: application/pdf creator: dernst date_created: 2023-07-31T08:11:20Z date_updated: 2023-07-31T08:11:20Z file_id: '13327' file_name: 2023_LNCS_CAV_HenzingerT.pdf file_size: 647760 relation: main_file success: 1 file_date_updated: 2023-07-31T08:11:20Z has_accepted_license: '1' intvolume: ' 13965' language: - iso: eng month: '07' oa: 1 oa_version: Published Version page: 358–382 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: Computer Aided Verification publication_identifier: eisbn: - '9783031377037' eissn: - 1611-3349 isbn: - '9783031377020' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' status: public title: Monitoring algorithmic fairness tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 13965 year: '2023' ... --- _id: '13221' abstract: - lang: eng text: The safety-liveness dichotomy is a fundamental concept in formal languages which plays a key role in verification. Recently, this dichotomy has been lifted to quantitative properties, which are arbitrary functions from infinite words to partially-ordered domains. We look into harnessing the dichotomy for the specific classes of quantitative properties expressed by quantitative automata. These automata contain finitely many states and rational-valued transition weights, and their common value functions Inf, Sup, LimInf, LimSup, LimInfAvg, LimSupAvg, and DSum map infinite words into the totallyordered domain of real numbers. In this automata-theoretic setting, we establish a connection between quantitative safety and topological continuity and provide an alternative characterization of quantitative safety and liveness in terms of their boolean counterparts. For all common value functions, we show how the safety closure of a quantitative automaton can be constructed in PTime, and we provide PSpace-complete checks of whether a given quantitative automaton is safe or live, with the exception of LimInfAvg and LimSupAvg automata, for which the safety check is in ExpSpace. Moreover, for deterministic Sup, LimInf, and LimSup automata, we give PTime decompositions into safe and live automata. These decompositions enable the separation of techniques for safety and liveness verification for quantitative specifications. acknowledgement: We thank Christof Löding for pointing us to some results on PSpace-hardess of universality problems and the anonymous reviewers for their helpful comments. This work was supported in part by the ERC-2020-AdG 101020093 and the Israel Science Foundation grant 2410/22. alternative_title: - LIPIcs article_number: '17' article_processing_charge: No author: - first_name: Udi full_name: Boker, Udi id: 31E297B6-F248-11E8-B48F-1D18A9856A87 last_name: Boker - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Nicolas Adrien full_name: Mazzocchi, Nicolas Adrien id: b26baa86-3308-11ec-87b0-8990f34baa85 last_name: Mazzocchi - first_name: Naci E full_name: Sarac, Naci E id: 8C6B42F8-C8E6-11E9-A03A-F2DCE5697425 last_name: Sarac citation: ama: 'Boker U, Henzinger TA, Mazzocchi NA, Sarac NE. Safety and liveness of quantitative automata. In: 34th International Conference on Concurrency Theory. Vol 279. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2023. doi:10.4230/LIPIcs.CONCUR.2023.17' apa: 'Boker, U., Henzinger, T. A., Mazzocchi, N. A., & Sarac, N. E. (2023). Safety and liveness of quantitative automata. In 34th International Conference on Concurrency Theory (Vol. 279). Antwerp, Belgium: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2023.17' chicago: Boker, Udi, Thomas A Henzinger, Nicolas Adrien Mazzocchi, and Naci E Sarac. “Safety and Liveness of Quantitative Automata.” In 34th International Conference on Concurrency Theory, Vol. 279. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023. https://doi.org/10.4230/LIPIcs.CONCUR.2023.17. ieee: U. Boker, T. A. Henzinger, N. A. Mazzocchi, and N. E. Sarac, “Safety and liveness of quantitative automata,” in 34th International Conference on Concurrency Theory, Antwerp, Belgium, 2023, vol. 279. ista: 'Boker U, Henzinger TA, Mazzocchi NA, Sarac NE. 2023. Safety and liveness of quantitative automata. 34th International Conference on Concurrency Theory. CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 279, 17.' mla: Boker, Udi, et al. “Safety and Liveness of Quantitative Automata.” 34th International Conference on Concurrency Theory, vol. 279, 17, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023, doi:10.4230/LIPIcs.CONCUR.2023.17. short: U. Boker, T.A. Henzinger, N.A. Mazzocchi, N.E. Sarac, in:, 34th International Conference on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023. conference: end_date: 2023-09-23 location: Antwerp, Belgium name: 'CONCUR: Conference on Concurrency Theory' start_date: 2023-09-18 date_created: 2023-07-14T10:00:15Z date_published: 2023-09-01T00:00:00Z date_updated: 2023-10-09T07:14:03Z day: '01' ddc: - '000' department: - _id: GradSch - _id: ToHe doi: 10.4230/LIPIcs.CONCUR.2023.17 ec_funded: 1 external_id: arxiv: - '2307.06016' file: - access_level: open_access checksum: d40e57a04448ea5c77d7e1cfb9590a81 content_type: application/pdf creator: esarac date_created: 2023-07-14T12:03:48Z date_updated: 2023-07-14T12:03:48Z file_id: '13224' file_name: CONCUR23.pdf file_size: 755529 relation: main_file success: 1 file_date_updated: 2023-07-14T12:03:48Z has_accepted_license: '1' intvolume: ' 279' language: - iso: eng month: '09' oa: 1 oa_version: Published Version project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 34th International Conference on Concurrency Theory publication_identifier: eissn: - 1868-8969 isbn: - '9783959772990' publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' status: public title: Safety and liveness of quantitative automata tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 279 year: '2023' ... --- _id: '14405' abstract: - lang: eng text: We introduce hypernode automata as a new specification formalism for hyperproperties of concurrent systems. They are finite automata with nodes labeled with hypernode logic formulas and transitions labeled with actions. A hypernode logic formula specifies relations between sequences of variable values in different system executions. Unlike HyperLTL, hypernode logic takes an asynchronous view on execution traces by constraining the values and the order of value changes of each variable without correlating the timing of the changes. Different execution traces are synchronized solely through the transitions of hypernode automata. Hypernode automata naturally combine asynchronicity at the node level with synchronicity at the transition level. We show that the model-checking problem for hypernode automata is decidable over action-labeled Kripke structures, whose actions induce transitions of the specification automata. For this reason, hypernode automaton is a suitable formalism for specifying and verifying asynchronous hyperproperties, such as declassifying observational determinism in multi-threaded programs. acknowledgement: "This work was supported in part by the Austrian Science Fund (FWF) SFB project\r\nSpyCoDe F8502, by the FWF projects ZK-35 and W1255-N23, and by the ERC Advanced Grant\r\nVAMOS 101020093." alternative_title: - LIPIcs article_number: '21' article_processing_charge: Yes author: - first_name: Ezio full_name: Bartocci, Ezio last_name: Bartocci - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Dejan full_name: Nickovic, Dejan id: 41BCEE5C-F248-11E8-B48F-1D18A9856A87 last_name: Nickovic - first_name: Ana full_name: Oliveira da Costa, Ana id: f347ec37-6676-11ee-b395-a888cb7b4fb4 last_name: Oliveira da Costa orcid: 0000-0002-8741-5799 citation: ama: 'Bartocci E, Henzinger TA, Nickovic D, Oliveira da Costa A. Hypernode automata. In: 34th International Conference on Concurrency Theory. Vol 279. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2023. doi:10.4230/LIPIcs.CONCUR.2023.21' apa: 'Bartocci, E., Henzinger, T. A., Nickovic, D., & Oliveira da Costa, A. (2023). Hypernode automata. In 34th International Conference on Concurrency Theory (Vol. 279). Antwerp, Belgium: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2023.21' chicago: Bartocci, Ezio, Thomas A Henzinger, Dejan Nickovic, and Ana Oliveira da Costa. “Hypernode Automata.” In 34th International Conference on Concurrency Theory, Vol. 279. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023. https://doi.org/10.4230/LIPIcs.CONCUR.2023.21. ieee: E. Bartocci, T. A. Henzinger, D. Nickovic, and A. Oliveira da Costa, “Hypernode automata,” in 34th International Conference on Concurrency Theory, Antwerp, Belgium, 2023, vol. 279. ista: 'Bartocci E, Henzinger TA, Nickovic D, Oliveira da Costa A. 2023. Hypernode automata. 34th International Conference on Concurrency Theory. CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 279, 21.' mla: Bartocci, Ezio, et al. “Hypernode Automata.” 34th International Conference on Concurrency Theory, vol. 279, 21, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023, doi:10.4230/LIPIcs.CONCUR.2023.21. short: E. Bartocci, T.A. Henzinger, D. Nickovic, A. Oliveira da Costa, in:, 34th International Conference on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023. conference: end_date: 2023-09-22 location: Antwerp, Belgium name: 'CONCUR: Conference on Concurrency Theory' start_date: 2023-09-19 date_created: 2023-10-08T22:01:16Z date_published: 2023-09-01T00:00:00Z date_updated: 2023-10-09T07:43:44Z day: '01' ddc: - '000' department: - _id: ToHe doi: 10.4230/LIPIcs.CONCUR.2023.21 ec_funded: 1 external_id: arxiv: - '2305.02836' file: - access_level: open_access checksum: 215765e40454d806174ac0a223e8d6fa content_type: application/pdf creator: dernst date_created: 2023-10-09T07:42:45Z date_updated: 2023-10-09T07:42:45Z file_id: '14413' file_name: 2023_LIPcs_Bartocci.pdf file_size: 795790 relation: main_file success: 1 file_date_updated: 2023-10-09T07:42:45Z has_accepted_license: '1' intvolume: ' 279' language: - iso: eng month: '09' oa: 1 oa_version: Published Version project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 34th International Conference on Concurrency Theory publication_identifier: isbn: - '9783959772990' issn: - '18688969' publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' scopus_import: '1' status: public title: Hypernode automata tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 279 year: '2023' ... --- _id: '14454' abstract: - lang: eng text: As AI and machine-learned software are used increasingly for making decisions that affect humans, it is imperative that they remain fair and unbiased in their decisions. To complement design-time bias mitigation measures, runtime verification techniques have been introduced recently to monitor the algorithmic fairness of deployed systems. Previous monitoring techniques assume full observability of the states of the (unknown) monitored system. Moreover, they can monitor only fairness properties that are specified as arithmetic expressions over the probabilities of different events. In this work, we extend fairness monitoring to systems modeled as partially observed Markov chains (POMC), and to specifications containing arithmetic expressions over the expected values of numerical functions on event sequences. The only assumptions we make are that the underlying POMC is aperiodic and starts in the stationary distribution, with a bound on its mixing time being known. These assumptions enable us to estimate a given property for the entire distribution of possible executions of the monitored POMC, by observing only a single execution. Our monitors observe a long run of the system and, after each new observation, output updated PAC-estimates of how fair or biased the system is. The monitors are computationally lightweight and, using a prototype implementation, we demonstrate their effectiveness on several real-world examples. acknowledgement: 'This work is supported by the European Research Council under Grant No.: ERC-2020-AdG 101020093.' alternative_title: - LNCS article_processing_charge: No author: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Konstantin full_name: Kueffner, Konstantin id: 8121a2d0-dc85-11ea-9058-af578f3b4515 last_name: Kueffner orcid: 0000-0001-8974-2542 - first_name: Kaushik full_name: Mallik, Kaushik id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598 last_name: Mallik orcid: 0000-0001-9864-7475 citation: ama: 'Henzinger TA, Kueffner K, Mallik K. Monitoring algorithmic fairness under partial observations. In: 23rd International Conference on Runtime Verification. Vol 14245. Springer Nature; 2023:291-311. doi:10.1007/978-3-031-44267-4_15' apa: 'Henzinger, T. A., Kueffner, K., & Mallik, K. (2023). Monitoring algorithmic fairness under partial observations. In 23rd International Conference on Runtime Verification (Vol. 14245, pp. 291–311). Thessaloniki, Greece: Springer Nature. https://doi.org/10.1007/978-3-031-44267-4_15' chicago: Henzinger, Thomas A, Konstantin Kueffner, and Kaushik Mallik. “Monitoring Algorithmic Fairness under Partial Observations.” In 23rd International Conference on Runtime Verification, 14245:291–311. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-44267-4_15. ieee: T. A. Henzinger, K. Kueffner, and K. Mallik, “Monitoring algorithmic fairness under partial observations,” in 23rd International Conference on Runtime Verification, Thessaloniki, Greece, 2023, vol. 14245, pp. 291–311. ista: 'Henzinger TA, Kueffner K, Mallik K. 2023. Monitoring algorithmic fairness under partial observations. 23rd International Conference on Runtime Verification. RV: Conference on Runtime Verification, LNCS, vol. 14245, 291–311.' mla: Henzinger, Thomas A., et al. “Monitoring Algorithmic Fairness under Partial Observations.” 23rd International Conference on Runtime Verification, vol. 14245, Springer Nature, 2023, pp. 291–311, doi:10.1007/978-3-031-44267-4_15. short: T.A. Henzinger, K. Kueffner, K. Mallik, in:, 23rd International Conference on Runtime Verification, Springer Nature, 2023, pp. 291–311. conference: end_date: 2023-10-06 location: Thessaloniki, Greece name: 'RV: Conference on Runtime Verification' start_date: 2023-10-03 date_created: 2023-10-29T23:01:15Z date_published: 2023-10-01T00:00:00Z date_updated: 2023-10-31T11:48:20Z day: '01' department: - _id: ToHe doi: 10.1007/978-3-031-44267-4_15 ec_funded: 1 external_id: arxiv: - '2308.00341' intvolume: ' 14245' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2308.00341 month: '10' oa: 1 oa_version: Preprint page: 291-311 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 23rd International Conference on Runtime Verification publication_identifier: eissn: - 1611-3349 isbn: - '9783031442667' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Monitoring algorithmic fairness under partial observations type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 14245 year: '2023' ... --- _id: '14518' abstract: - lang: eng text: We consider bidding games, a class of two-player zero-sum graph games. The game proceeds as follows. Both players have bounded budgets. A token is placed on a vertex of a graph, in each turn the players simultaneously submit bids, and the higher bidder moves the token, where we break bidding ties in favor of Player 1. Player 1 wins the game iff the token visits a designated target vertex. We consider, for the first time, poorman discrete-bidding in which the granularity of the bids is restricted and the higher bid is paid to the bank. Previous work either did not impose granularity restrictions or considered Richman bidding (bids are paid to the opponent). While the latter mechanisms are technically more accessible, the former is more appealing from a practical standpoint. Our study focuses on threshold budgets, which is the necessary and sufficient initial budget required for Player 1 to ensure winning against a given Player 2 budget. We first show existence of thresholds. In DAGs, we show that threshold budgets can be approximated with error bounds by thresholds under continuous-bidding and that they exhibit a periodic behavior. We identify closed-form solutions in special cases. We implement and experiment with an algorithm to find threshold budgets. acknowledgement: This research was supported in part by ISF grant no. 1679/21, ERC CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation programme under the Marie SkłodowskaCurie Grant Agreement No. 665385. article_processing_charge: No author: - first_name: Guy full_name: Avni, Guy id: 463C8BC2-F248-11E8-B48F-1D18A9856A87 last_name: Avni orcid: 0000-0001-5588-8287 - first_name: Tobias full_name: Meggendorfer, Tobias id: b21b0c15-30a2-11eb-80dc-f13ca25802e1 last_name: Meggendorfer orcid: 0000-0002-1712-2165 - first_name: Suman full_name: Sadhukhan, Suman last_name: Sadhukhan - first_name: Josef full_name: Tkadlec, Josef id: 3F24CCC8-F248-11E8-B48F-1D18A9856A87 last_name: Tkadlec orcid: 0000-0002-1097-9684 - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 citation: ama: 'Avni G, Meggendorfer T, Sadhukhan S, Tkadlec J, Zikelic D. Reachability poorman discrete-bidding games. In: Frontiers in Artificial Intelligence and Applications. Vol 372. IOS Press; 2023:141-148. doi:10.3233/FAIA230264' apa: 'Avni, G., Meggendorfer, T., Sadhukhan, S., Tkadlec, J., & Zikelic, D. (2023). Reachability poorman discrete-bidding games. In Frontiers in Artificial Intelligence and Applications (Vol. 372, pp. 141–148). Krakow, Poland: IOS Press. https://doi.org/10.3233/FAIA230264' chicago: Avni, Guy, Tobias Meggendorfer, Suman Sadhukhan, Josef Tkadlec, and Dorde Zikelic. “Reachability Poorman Discrete-Bidding Games.” In Frontiers in Artificial Intelligence and Applications, 372:141–48. IOS Press, 2023. https://doi.org/10.3233/FAIA230264. ieee: G. Avni, T. Meggendorfer, S. Sadhukhan, J. Tkadlec, and D. Zikelic, “Reachability poorman discrete-bidding games,” in Frontiers in Artificial Intelligence and Applications, Krakow, Poland, 2023, vol. 372, pp. 141–148. ista: 'Avni G, Meggendorfer T, Sadhukhan S, Tkadlec J, Zikelic D. 2023. Reachability poorman discrete-bidding games. Frontiers in Artificial Intelligence and Applications. ECAI: European Conference on Artificial Intelligence vol. 372, 141–148.' mla: Avni, Guy, et al. “Reachability Poorman Discrete-Bidding Games.” Frontiers in Artificial Intelligence and Applications, vol. 372, IOS Press, 2023, pp. 141–48, doi:10.3233/FAIA230264. short: G. Avni, T. Meggendorfer, S. Sadhukhan, J. Tkadlec, D. Zikelic, in:, Frontiers in Artificial Intelligence and Applications, IOS Press, 2023, pp. 141–148. conference: end_date: 2023-10-04 location: Krakow, Poland name: 'ECAI: European Conference on Artificial Intelligence' start_date: 2023-09-30 date_created: 2023-11-12T23:00:56Z date_published: 2023-09-28T00:00:00Z date_updated: 2023-11-13T10:18:45Z day: '28' ddc: - '000' department: - _id: ToHe - _id: KrCh doi: 10.3233/FAIA230264 ec_funded: 1 external_id: arxiv: - '2307.15218' file: - access_level: open_access checksum: 1390ca38480fa4cf286b0f1a42e8c12f content_type: application/pdf creator: dernst date_created: 2023-11-13T10:16:10Z date_updated: 2023-11-13T10:16:10Z file_id: '14529' file_name: 2023_FAIA_Avni.pdf file_size: 501011 relation: main_file success: 1 file_date_updated: 2023-11-13T10:16:10Z has_accepted_license: '1' intvolume: ' 372' language: - iso: eng license: https://creativecommons.org/licenses/by-nc/4.0/ month: '09' oa: 1 oa_version: Published Version page: 141-148 project: - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' publication: Frontiers in Artificial Intelligence and Applications publication_identifier: isbn: - '9781643684369' issn: - 0922-6389 publication_status: published publisher: IOS Press quality_controlled: '1' scopus_import: '1' status: public title: Reachability poorman discrete-bidding games tmp: image: /images/cc_by_nc.png legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) short: CC BY-NC (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 372 year: '2023' ... --- _id: '14559' abstract: - lang: eng text: We consider the problem of learning control policies in discrete-time stochastic systems which guarantee that the system stabilizes within some specified stabilization region with probability 1. Our approach is based on the novel notion of stabilizing ranking supermartingales (sRSMs) that we introduce in this work. Our sRSMs overcome the limitation of methods proposed in previous works whose applicability is restricted to systems in which the stabilizing region cannot be left once entered under any control policy. We present a learning procedure that learns a control policy together with an sRSM that formally certifies probability 1 stability, both learned as neural networks. We show that this procedure can also be adapted to formally verifying that, under a given Lipschitz continuous control policy, the stochastic system stabilizes within some stabilizing region with probability 1. Our experimental evaluation shows that our learning procedure can successfully learn provably stabilizing policies in practice. acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. alternative_title: - LNCS article_processing_charge: No author: - first_name: Matin full_name: Ansaripour, Matin last_name: Ansaripour - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 citation: ama: 'Ansaripour M, Chatterjee K, Henzinger TA, Lechner M, Zikelic D. Learning provably stabilizing neural controllers for discrete-time stochastic systems. In: 21st International Symposium on Automated Technology for Verification and Analysis. Vol 14215. Springer Nature; 2023:357-379. doi:10.1007/978-3-031-45329-8_17' apa: 'Ansaripour, M., Chatterjee, K., Henzinger, T. A., Lechner, M., & Zikelic, D. (2023). Learning provably stabilizing neural controllers for discrete-time stochastic systems. In 21st International Symposium on Automated Technology for Verification and Analysis (Vol. 14215, pp. 357–379). Singapore, Singapore: Springer Nature. https://doi.org/10.1007/978-3-031-45329-8_17' chicago: Ansaripour, Matin, Krishnendu Chatterjee, Thomas A Henzinger, Mathias Lechner, and Dorde Zikelic. “Learning Provably Stabilizing Neural Controllers for Discrete-Time Stochastic Systems.” In 21st International Symposium on Automated Technology for Verification and Analysis, 14215:357–79. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-45329-8_17. ieee: M. Ansaripour, K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic, “Learning provably stabilizing neural controllers for discrete-time stochastic systems,” in 21st International Symposium on Automated Technology for Verification and Analysis, Singapore, Singapore, 2023, vol. 14215, pp. 357–379. ista: 'Ansaripour M, Chatterjee K, Henzinger TA, Lechner M, Zikelic D. 2023. Learning provably stabilizing neural controllers for discrete-time stochastic systems. 21st International Symposium on Automated Technology for Verification and Analysis. ATVA: Automated Technology for Verification and Analysis, LNCS, vol. 14215, 357–379.' mla: Ansaripour, Matin, et al. “Learning Provably Stabilizing Neural Controllers for Discrete-Time Stochastic Systems.” 21st International Symposium on Automated Technology for Verification and Analysis, vol. 14215, Springer Nature, 2023, pp. 357–79, doi:10.1007/978-3-031-45329-8_17. short: M. Ansaripour, K. Chatterjee, T.A. Henzinger, M. Lechner, D. Zikelic, in:, 21st International Symposium on Automated Technology for Verification and Analysis, Springer Nature, 2023, pp. 357–379. conference: end_date: 2023-10-27 location: Singapore, Singapore name: 'ATVA: Automated Technology for Verification and Analysis' start_date: 2023-10-24 date_created: 2023-11-19T23:00:56Z date_published: 2023-10-22T00:00:00Z date_updated: 2023-11-20T08:30:20Z day: '22' department: - _id: ToHe - _id: KrCh doi: 10.1007/978-3-031-45329-8_17 ec_funded: 1 intvolume: ' 14215' language: - iso: eng month: '10' oa_version: None page: 357-379 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: 21st International Symposium on Automated Technology for Verification and Analysis publication_identifier: eissn: - 1611-3349 isbn: - '9783031453281' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Learning provably stabilizing neural controllers for discrete-time stochastic systems type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 14215 year: '2023' ... --- _id: '13228' abstract: - lang: eng text: A machine-learned system that is fair in static decision-making tasks may have biased societal impacts in the long-run. This may happen when the system interacts with humans and feedback patterns emerge, reinforcing old biases in the system and creating new biases. While existing works try to identify and mitigate long-run biases through smart system design, we introduce techniques for monitoring fairness in real time. Our goal is to build and deploy a monitor that will continuously observe a long sequence of events generated by the system in the wild, and will output, with each event, a verdict on how fair the system is at the current point in time. The advantages of monitoring are two-fold. Firstly, fairness is evaluated at run-time, which is important because unfair behaviors may not be eliminated a priori, at design-time, due to partial knowledge about the system and the environment, as well as uncertainties and dynamic changes in the system and the environment, such as the unpredictability of human behavior. Secondly, monitors are by design oblivious to how the monitored system is constructed, which makes them suitable to be used as trusted third-party fairness watchdogs. They function as computationally lightweight statistical estimators, and their correctness proofs rely on the rigorous analysis of the stochastic process that models the assumptions about the underlying dynamics of the system. We show, both in theory and experiments, how monitors can warn us (1) if a bank’s credit policy over time has created an unfair distribution of credit scores among the population, and (2) if a resource allocator’s allocation policy over time has made unfair allocations. Our experiments demonstrate that the monitors introduce very low overhead. We believe that runtime monitoring is an important and mathematically rigorous new addition to the fairness toolbox. acknowledgement: 'The authors would like to thank the anonymous reviewers for their valuable comments and helpful suggestions. This work is supported by the European Research Council under Grant No.: ERC-2020-AdG 101020093.' article_processing_charge: No author: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Mahyar full_name: Karimi, Mahyar last_name: Karimi - first_name: Konstantin full_name: Kueffner, Konstantin id: 8121a2d0-dc85-11ea-9058-af578f3b4515 last_name: Kueffner orcid: 0000-0001-8974-2542 - first_name: Kaushik full_name: Mallik, Kaushik id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598 last_name: Mallik orcid: 0000-0001-9864-7475 citation: ama: 'Henzinger TA, Karimi M, Kueffner K, Mallik K. Runtime monitoring of dynamic fairness properties. In: FAccT ’23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency. Association for Computing Machinery; 2023:604-614. doi:10.1145/3593013.3594028' apa: 'Henzinger, T. A., Karimi, M., Kueffner, K., & Mallik, K. (2023). Runtime monitoring of dynamic fairness properties. In FAccT ’23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (pp. 604–614). Chicago, IL, United States: Association for Computing Machinery. https://doi.org/10.1145/3593013.3594028' chicago: 'Henzinger, Thomas A, Mahyar Karimi, Konstantin Kueffner, and Kaushik Mallik. “Runtime Monitoring of Dynamic Fairness Properties.” In FAccT ’23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 604–14. Association for Computing Machinery, 2023. https://doi.org/10.1145/3593013.3594028.' ieee: 'T. A. Henzinger, M. Karimi, K. Kueffner, and K. Mallik, “Runtime monitoring of dynamic fairness properties,” in FAccT ’23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, Chicago, IL, United States, 2023, pp. 604–614.' ista: 'Henzinger TA, Karimi M, Kueffner K, Mallik K. 2023. Runtime monitoring of dynamic fairness properties. FAccT ’23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency. FAccT: Conference on Fairness, Accountability and Transparency, 604–614.' mla: 'Henzinger, Thomas A., et al. “Runtime Monitoring of Dynamic Fairness Properties.” FAccT ’23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, Association for Computing Machinery, 2023, pp. 604–14, doi:10.1145/3593013.3594028.' short: 'T.A. Henzinger, M. Karimi, K. Kueffner, K. Mallik, in:, FAccT ’23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, Association for Computing Machinery, 2023, pp. 604–614.' conference: end_date: 2023-06-15 location: Chicago, IL, United States name: 'FAccT: Conference on Fairness, Accountability and Transparency' start_date: 2023-06-12 date_created: 2023-07-16T22:01:09Z date_published: 2023-06-12T00:00:00Z date_updated: 2023-12-13T11:30:31Z day: '12' ddc: - '000' department: - _id: ToHe doi: 10.1145/3593013.3594028 ec_funded: 1 external_id: arxiv: - '2305.04699' isi: - '001062819300057' file: - access_level: open_access checksum: 96c759db9cdf94b81e37871a66a6ff48 content_type: application/pdf creator: dernst date_created: 2023-07-18T07:43:10Z date_updated: 2023-07-18T07:43:10Z file_id: '13245' file_name: 2023_ACM_HenzingerT.pdf file_size: 4100596 relation: main_file success: 1 file_date_updated: 2023-07-18T07:43:10Z has_accepted_license: '1' isi: 1 language: - iso: eng month: '06' oa: 1 oa_version: Published Version page: 604-614 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 'FAccT ''23: Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency' publication_identifier: isbn: - '9781450372527' publication_status: published publisher: Association for Computing Machinery quality_controlled: '1' scopus_import: '1' status: public title: Runtime monitoring of dynamic fairness properties tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2023' ... --- _id: '13263' abstract: - lang: eng text: "Motivation: Boolean networks are simple but efficient mathematical formalism for modelling complex biological systems. However, having only two levels of activation is sometimes not enough to fully capture the dynamics of real-world biological systems. Hence, the need for multi-valued networks (MVNs), a generalization of Boolean networks. Despite the importance of MVNs for modelling biological systems, only limited progress has been made on developing theories, analysis methods, and tools that can support them. In particular, the recent use of trap spaces in Boolean networks made a great impact on the field of systems biology, but there has been no similar concept defined and studied for MVNs to date.\r\n\r\nResults: In this work, we generalize the concept of trap spaces in Boolean networks to that in MVNs. We then develop the theory and the analysis methods for trap spaces in MVNs. In particular, we implement all proposed methods in a Python package called trapmvn. Not only showing the applicability of our approach via a realistic case study, we also evaluate the time efficiency of the method on a large collection of real-world models. The experimental results confirm the time efficiency, which we believe enables more accurate analysis on larger and more complex multi-valued models." acknowledgement: This work was supported by L’Institut Carnot STAR, Marseille, France, and by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. [101034413]. article_processing_charge: Yes article_type: original author: - first_name: Van Giang full_name: Trinh, Van Giang last_name: Trinh - first_name: Belaid full_name: Benhamou, Belaid last_name: Benhamou - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Samuel full_name: Pastva, Samuel id: 07c5ea74-f61c-11ec-a664-aa7c5d957b2b last_name: Pastva orcid: 0000-0003-1993-0331 citation: ama: 'Trinh VG, Benhamou B, Henzinger TA, Pastva S. Trap spaces of multi-valued networks: Definition, computation, and applications. Bioinformatics. 2023;39(Supplement_1):i513-i522. doi:10.1093/bioinformatics/btad262' apa: 'Trinh, V. G., Benhamou, B., Henzinger, T. A., & Pastva, S. (2023). Trap spaces of multi-valued networks: Definition, computation, and applications. Bioinformatics. Oxford Academic. https://doi.org/10.1093/bioinformatics/btad262' chicago: 'Trinh, Van Giang, Belaid Benhamou, Thomas A Henzinger, and Samuel Pastva. “Trap Spaces of Multi-Valued Networks: Definition, Computation, and Applications.” Bioinformatics. Oxford Academic, 2023. https://doi.org/10.1093/bioinformatics/btad262.' ieee: 'V. G. Trinh, B. Benhamou, T. A. Henzinger, and S. Pastva, “Trap spaces of multi-valued networks: Definition, computation, and applications,” Bioinformatics, vol. 39, no. Supplement_1. Oxford Academic, pp. i513–i522, 2023.' ista: 'Trinh VG, Benhamou B, Henzinger TA, Pastva S. 2023. Trap spaces of multi-valued networks: Definition, computation, and applications. Bioinformatics. 39(Supplement_1), i513–i522.' mla: 'Trinh, Van Giang, et al. “Trap Spaces of Multi-Valued Networks: Definition, Computation, and Applications.” Bioinformatics, vol. 39, no. Supplement_1, Oxford Academic, 2023, pp. i513–22, doi:10.1093/bioinformatics/btad262.' short: V.G. Trinh, B. Benhamou, T.A. Henzinger, S. Pastva, Bioinformatics 39 (2023) i513–i522. date_created: 2023-07-23T22:01:12Z date_published: 2023-06-30T00:00:00Z date_updated: 2023-12-13T11:41:52Z day: '30' ddc: - '000' department: - _id: ToHe doi: 10.1093/bioinformatics/btad262 ec_funded: 1 external_id: isi: - '001027457000060' pmid: - '37387165' file: - access_level: open_access checksum: ba3abe1171df1958413b7c7f957f5486 content_type: application/pdf creator: dernst date_created: 2023-07-31T11:09:05Z date_updated: 2023-07-31T11:09:05Z file_id: '13335' file_name: 2023_Bioinformatics_Trinh.pdf file_size: 641736 relation: main_file success: 1 file_date_updated: 2023-07-31T11:09:05Z has_accepted_license: '1' intvolume: ' 39' isi: 1 issue: Supplement_1 language: - iso: eng month: '06' oa: 1 oa_version: Published Version page: i513-i522 pmid: 1 project: - _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c call_identifier: H2020 grant_number: '101034413' name: 'IST-BRIDGE: International postdoctoral program' publication: Bioinformatics publication_identifier: eissn: - 1367-4811 issn: - 1367-4803 publication_status: published publisher: Oxford Academic quality_controlled: '1' related_material: link: - relation: software url: https://github.com/giang-trinh/trap-mvn scopus_import: '1' status: public title: 'Trap spaces of multi-valued networks: Definition, computation, and applications' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 39 year: '2023' ... --- _id: '14400' abstract: - lang: eng text: "We consider the problem of computing the maximal probability of satisfying an \r\n-regular specification for stochastic, continuous-state, nonlinear systems evolving in discrete time. The problem reduces, after automata-theoretic constructions, to finding the maximal probability of satisfying a parity condition on a (possibly hybrid) state space. While characterizing the exact satisfaction probability is open, we show that a lower bound on this probability can be obtained by (I) computing an under-approximation of the qualitative winning region, i.e., states from which the parity condition can be enforced almost surely, and (II) computing the maximal probability of reaching this qualitative winning region.\r\nThe heart of our approach is a technique to symbolically compute the under-approximation of the qualitative winning region in step (I) via a finite-state abstraction of the original system as a \r\n-player parity game. Our abstraction procedure uses only the support of the probabilistic evolution; it does not use precise numerical transition probabilities. We prove that the winning set in the abstract -player game induces an under-approximation of the qualitative winning region in the original synthesis problem, along with a policy to solve it. By combining these contributions with (a) a symbolic fixpoint algorithm to solve \r\n-player games and (b) existing techniques for reachability policy synthesis in stochastic nonlinear systems, we get an abstraction-based algorithm for finding a lower bound on the maximal satisfaction probability.\r\nWe have implemented the abstraction-based algorithm in Mascot-SDS, where we combined the outlined abstraction step with our tool Genie (Majumdar et al., 2023) that solves \r\n-player parity games (through a reduction to Rabin games) more efficiently than existing algorithms. We evaluated our implementation on the nonlinear model of a perturbed bistable switch from the literature. We show empirically that the lower bound on the winning region computed by our approach is precise, by comparing against an over-approximation of the qualitative winning region. Moreover, our implementation outperforms a recently proposed tool for solving this problem by a large margin." acknowledgement: "We thank Daniel Hausmann and Nir Piterman for their valuable comments on an earlier version of the manuscript of our other paper [22] where we present, among other things, the parity fixpoint for 2 1/2-player games (for a slightly more general class of games) with a different and indirect proof of correctness. Based on their comments we observed that, unlike the other fixpoints that we present in [22], the parity fixpoint does not follow the exact same structure as its counterpart for 2-player games, which we also use int his paper.\r\nWe also thank Thejaswini Raghavan for observing that our symbolic parity fixpoint algorithm can be solved in quasi-polynomial time using recent improved algorithms for solving \r\n-calculus expressions. This significantly improved the complexity bounds of our algorithm in this paper.\r\nThe work of R. Majumdar and A.-K. Schmuck are partially supported by DFG, Germany project 389792660 TRR 248–CPEC. A.-K. Schmuck is additionally funded through DFG, Germany project (SCHM 3541/1-1). K. Mallik is supported by the ERC project ERC-2020-AdG 101020093. S. Soudjani is supported by the following projects: EPSRC EP/V043676/1, EIC 101070802, and ERC 101089047." article_number: '101430' article_processing_charge: No article_type: original author: - first_name: Rupak full_name: Majumdar, Rupak last_name: Majumdar - first_name: Kaushik full_name: Mallik, Kaushik id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598 last_name: Mallik orcid: 0000-0001-9864-7475 - first_name: Anne Kathrin full_name: Schmuck, Anne Kathrin last_name: Schmuck - first_name: Sadegh full_name: Soudjani, Sadegh last_name: Soudjani citation: ama: 'Majumdar R, Mallik K, Schmuck AK, Soudjani S. Symbolic control for stochastic systems via finite parity games. Nonlinear Analysis: Hybrid Systems. 2023;51. doi:10.1016/j.nahs.2023.101430' apa: 'Majumdar, R., Mallik, K., Schmuck, A. K., & Soudjani, S. (2023). Symbolic control for stochastic systems via finite parity games. Nonlinear Analysis: Hybrid Systems. Elsevier. https://doi.org/10.1016/j.nahs.2023.101430' chicago: 'Majumdar, Rupak, Kaushik Mallik, Anne Kathrin Schmuck, and Sadegh Soudjani. “Symbolic Control for Stochastic Systems via Finite Parity Games.” Nonlinear Analysis: Hybrid Systems. Elsevier, 2023. https://doi.org/10.1016/j.nahs.2023.101430.' ieee: 'R. Majumdar, K. Mallik, A. K. Schmuck, and S. Soudjani, “Symbolic control for stochastic systems via finite parity games,” Nonlinear Analysis: Hybrid Systems, vol. 51. Elsevier, 2023.' ista: 'Majumdar R, Mallik K, Schmuck AK, Soudjani S. 2023. Symbolic control for stochastic systems via finite parity games. Nonlinear Analysis: Hybrid Systems. 51, 101430.' mla: 'Majumdar, Rupak, et al. “Symbolic Control for Stochastic Systems via Finite Parity Games.” Nonlinear Analysis: Hybrid Systems, vol. 51, 101430, Elsevier, 2023, doi:10.1016/j.nahs.2023.101430.' short: 'R. Majumdar, K. Mallik, A.K. Schmuck, S. Soudjani, Nonlinear Analysis: Hybrid Systems 51 (2023).' date_created: 2023-10-08T22:01:15Z date_published: 2023-09-27T00:00:00Z date_updated: 2023-12-13T12:58:56Z day: '27' department: - _id: ToHe doi: 10.1016/j.nahs.2023.101430 ec_funded: 1 external_id: arxiv: - '2101.00834' isi: - '001093188100001' intvolume: ' 51' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.1016/j.nahs.2023.101430 month: '09' oa: 1 oa_version: Published Version project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 'Nonlinear Analysis: Hybrid Systems' publication_identifier: issn: - 1751-570X publication_status: epub_ahead publisher: Elsevier quality_controlled: '1' scopus_import: '1' status: public title: Symbolic control for stochastic systems via finite parity games type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 51 year: '2023' ... --- _id: '14718' abstract: - lang: eng text: 'Binary decision diagrams (BDDs) are one of the fundamental data structures in formal methods and computer science in general. However, the performance of BDD-based algorithms greatly depends on memory latency due to the reliance on large hash tables and thus, by extension, on the speed of random memory access. This hinders the full utilisation of resources available on modern CPUs, since the absolute memory latency has not improved significantly for at least a decade. In this paper, we explore several implementation techniques that improve the performance of BDD manipulation either through enhanced memory locality or by partially eliminating random memory access. On a benchmark suite of 600+ BDDs derived from real-world applications, we demonstrate runtime that is comparable or better than parallelising the same operations on eight CPU cores. ' acknowledgement: "This work was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101034413 and the\r\n“VAMOS” grant ERC-2020-AdG 101020093." article_processing_charge: No author: - first_name: Samuel full_name: Pastva, Samuel id: 07c5ea74-f61c-11ec-a664-aa7c5d957b2b last_name: Pastva orcid: 0000-0003-1993-0331 - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: 'Pastva S, Henzinger TA. Binary decision diagrams on modern hardware. In: Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design. TU Vienna Academic Press; 2023:122-131. doi:10.34727/2023/isbn.978-3-85448-060-0_20' apa: 'Pastva, S., & Henzinger, T. A. (2023). Binary decision diagrams on modern hardware. In Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design (pp. 122–131). Ames, IA, United States: TU Vienna Academic Press. https://doi.org/10.34727/2023/isbn.978-3-85448-060-0_20' chicago: Pastva, Samuel, and Thomas A Henzinger. “Binary Decision Diagrams on Modern Hardware.” In Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design, 122–31. TU Vienna Academic Press, 2023. https://doi.org/10.34727/2023/isbn.978-3-85448-060-0_20. ieee: S. Pastva and T. A. Henzinger, “Binary decision diagrams on modern hardware,” in Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design, Ames, IA, United States, 2023, pp. 122–131. ista: 'Pastva S, Henzinger TA. 2023. Binary decision diagrams on modern hardware. Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design. FMCAD: Conference on Formal Methods in Computer-aided design, 122–131.' mla: Pastva, Samuel, and Thomas A. Henzinger. “Binary Decision Diagrams on Modern Hardware.” Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design, TU Vienna Academic Press, 2023, pp. 122–31, doi:10.34727/2023/isbn.978-3-85448-060-0_20. short: S. Pastva, T.A. Henzinger, in:, Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design, TU Vienna Academic Press, 2023, pp. 122–131. conference: end_date: 2023-10-27 location: Ames, IA, United States name: 'FMCAD: Conference on Formal Methods in Computer-aided design' start_date: 2023-10-25 date_created: 2023-12-31T23:01:03Z date_published: 2023-10-01T00:00:00Z date_updated: 2024-01-02T08:16:28Z day: '01' ddc: - '000' department: - _id: ToHe doi: 10.34727/2023/isbn.978-3-85448-060-0_20 ec_funded: 1 file: - access_level: open_access checksum: 818d6e13dd508f3a04f0941081022e5d content_type: application/pdf creator: dernst date_created: 2024-01-02T08:14:23Z date_updated: 2024-01-02T08:14:23Z file_id: '14721' file_name: 2023_FMCAD_Pastva.pdf file_size: 524321 relation: main_file success: 1 file_date_updated: 2024-01-02T08:14:23Z has_accepted_license: '1' language: - iso: eng month: '10' oa: 1 oa_version: Published Version page: 122-131 project: - _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c call_identifier: H2020 grant_number: '101034413' name: 'IST-BRIDGE: International postdoctoral program' - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design publication_identifier: isbn: - '9783854480600' publication_status: published publisher: TU Vienna Academic Press quality_controlled: '1' scopus_import: '1' status: public title: Binary decision diagrams on modern hardware tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2023' ... --- _id: '14830' abstract: - lang: eng text: We study the problem of learning controllers for discrete-time non-linear stochastic dynamical systems with formal reach-avoid guarantees. This work presents the first method for providing formal reach-avoid guarantees, which combine and generalize stability and safety guarantees, with a tolerable probability threshold p in [0,1] over the infinite time horizon. Our method leverages advances in machine learning literature and it represents formal certificates as neural networks. In particular, we learn a certificate in the form of a reach-avoid supermartingale (RASM), a novel notion that we introduce in this work. Our RASMs provide reachability and avoidance guarantees by imposing constraints on what can be viewed as a stochastic extension of level sets of Lyapunov functions for deterministic systems. Our approach solves several important problems -- it can be used to learn a control policy from scratch, to verify a reach-avoid specification for a fixed control policy, or to fine-tune a pre-trained policy if it does not satisfy the reach-avoid specification. We validate our approach on 3 stochastic non-linear reinforcement learning tasks. acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. article_processing_charge: No author: - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X citation: ama: 'Zikelic D, Lechner M, Henzinger TA, Chatterjee K. Learning control policies for stochastic systems with reach-avoid guarantees. In: Proceedings of the 37th AAAI Conference on Artificial Intelligence. Vol 37. Association for the Advancement of Artificial Intelligence; 2023:11926-11935. doi:10.1609/aaai.v37i10.26407' apa: 'Zikelic, D., Lechner, M., Henzinger, T. A., & Chatterjee, K. (2023). Learning control policies for stochastic systems with reach-avoid guarantees. In Proceedings of the 37th AAAI Conference on Artificial Intelligence (Vol. 37, pp. 11926–11935). Washington, DC, United States: Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v37i10.26407' chicago: Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” In Proceedings of the 37th AAAI Conference on Artificial Intelligence, 37:11926–35. Association for the Advancement of Artificial Intelligence, 2023. https://doi.org/10.1609/aaai.v37i10.26407. ieee: D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control policies for stochastic systems with reach-avoid guarantees,” in Proceedings of the 37th AAAI Conference on Artificial Intelligence, Washington, DC, United States, 2023, vol. 37, no. 10, pp. 11926–11935. ista: 'Zikelic D, Lechner M, Henzinger TA, Chatterjee K. 2023. Learning control policies for stochastic systems with reach-avoid guarantees. Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial Intelligence vol. 37, 11926–11935.' mla: Zikelic, Dorde, et al. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” Proceedings of the 37th AAAI Conference on Artificial Intelligence, vol. 37, no. 10, Association for the Advancement of Artificial Intelligence, 2023, pp. 11926–35, doi:10.1609/aaai.v37i10.26407. short: D. Zikelic, M. Lechner, T.A. Henzinger, K. Chatterjee, in:, Proceedings of the 37th AAAI Conference on Artificial Intelligence, Association for the Advancement of Artificial Intelligence, 2023, pp. 11926–11935. conference: end_date: 2023-02-14 location: Washington, DC, United States name: 'AAAI: Conference on Artificial Intelligence' start_date: 2023-02-07 date_created: 2024-01-18T07:44:31Z date_published: 2023-06-26T00:00:00Z date_updated: 2024-01-22T14:08:29Z day: '26' department: - _id: ToHe - _id: KrCh doi: 10.1609/aaai.v37i10.26407 ec_funded: 1 external_id: arxiv: - '2210.05308' intvolume: ' 37' issue: '10' keyword: - General Medicine language: - iso: eng month: '06' oa_version: Preprint page: 11926-11935 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: Proceedings of the 37th AAAI Conference on Artificial Intelligence publication_identifier: eissn: - 2374-3468 issn: - 2159-5399 publication_status: published publisher: Association for the Advancement of Artificial Intelligence quality_controlled: '1' related_material: record: - id: '14600' relation: earlier_version status: public status: public title: Learning control policies for stochastic systems with reach-avoid guarantees type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 37 year: '2023' ... --- _id: '13234' abstract: - lang: eng text: Neural-network classifiers achieve high accuracy when predicting the class of an input that they were trained to identify. Maintaining this accuracy in dynamic environments, where inputs frequently fall outside the fixed set of initially known classes, remains a challenge. We consider the problem of monitoring the classification decisions of neural networks in the presence of novel classes. For this purpose, we generalize our recently proposed abstraction-based monitor from binary output to real-valued quantitative output. This quantitative output enables new applications, two of which we investigate in the paper. As our first application, we introduce an algorithmic framework for active monitoring of a neural network, which allows us to learn new classes dynamically and yet maintain high monitoring performance. As our second application, we present an offline procedure to retrain the neural network to improve the monitor’s detection performance without deteriorating the network’s classification accuracy. Our experimental evaluation demonstrates both the benefits of our active monitoring framework in dynamic scenarios and the effectiveness of the retraining procedure. acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, by DIREC - Digital Research Centre Denmark, and by the Villum Investigator Grant S4OS. article_processing_charge: Yes (in subscription journal) article_type: original author: - first_name: Konstantin full_name: Kueffner, Konstantin id: 8121a2d0-dc85-11ea-9058-af578f3b4515 last_name: Kueffner orcid: 0000-0001-8974-2542 - first_name: Anna full_name: Lukina, Anna id: CBA4D1A8-0FE8-11E9-BDE6-07BFE5697425 last_name: Lukina - first_name: Christian full_name: Schilling, Christian id: 3A2F4DCE-F248-11E8-B48F-1D18A9856A87 last_name: Schilling orcid: 0000-0003-3658-1065 - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: 'Kueffner K, Lukina A, Schilling C, Henzinger TA. Into the unknown: Active monitoring of neural networks (extended version). International Journal on Software Tools for Technology Transfer. 2023;25:575-592. doi:10.1007/s10009-023-00711-4' apa: 'Kueffner, K., Lukina, A., Schilling, C., & Henzinger, T. A. (2023). Into the unknown: Active monitoring of neural networks (extended version). International Journal on Software Tools for Technology Transfer. Springer Nature. https://doi.org/10.1007/s10009-023-00711-4' chicago: 'Kueffner, Konstantin, Anna Lukina, Christian Schilling, and Thomas A Henzinger. “Into the Unknown: Active Monitoring of Neural Networks (Extended Version).” International Journal on Software Tools for Technology Transfer. Springer Nature, 2023. https://doi.org/10.1007/s10009-023-00711-4.' ieee: 'K. Kueffner, A. Lukina, C. Schilling, and T. A. Henzinger, “Into the unknown: Active monitoring of neural networks (extended version),” International Journal on Software Tools for Technology Transfer, vol. 25. Springer Nature, pp. 575–592, 2023.' ista: 'Kueffner K, Lukina A, Schilling C, Henzinger TA. 2023. Into the unknown: Active monitoring of neural networks (extended version). International Journal on Software Tools for Technology Transfer. 25, 575–592.' mla: 'Kueffner, Konstantin, et al. “Into the Unknown: Active Monitoring of Neural Networks (Extended Version).” International Journal on Software Tools for Technology Transfer, vol. 25, Springer Nature, 2023, pp. 575–92, doi:10.1007/s10009-023-00711-4.' short: K. Kueffner, A. Lukina, C. Schilling, T.A. Henzinger, International Journal on Software Tools for Technology Transfer 25 (2023) 575–592. date_created: 2023-07-16T22:01:11Z date_published: 2023-08-01T00:00:00Z date_updated: 2024-01-30T12:06:57Z day: '01' ddc: - '000' department: - _id: ToHe doi: 10.1007/s10009-023-00711-4 ec_funded: 1 external_id: arxiv: - '2009.06429' isi: - '001020160000001' file: - access_level: open_access checksum: 3c4b347f39412a76872f9a6f30101f94 content_type: application/pdf creator: dernst date_created: 2024-01-30T12:06:07Z date_updated: 2024-01-30T12:06:07Z file_id: '14903' file_name: 2023_JourSoftwareTools_Kueffner.pdf file_size: 13387667 relation: main_file success: 1 file_date_updated: 2024-01-30T12:06:07Z has_accepted_license: '1' intvolume: ' 25' isi: 1 language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: 575-592 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: International Journal on Software Tools for Technology Transfer publication_identifier: eissn: - 1433-2787 issn: - 1433-2779 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: record: - id: '10206' relation: shorter_version status: public scopus_import: '1' status: public title: 'Into the unknown: Active monitoring of neural networks (extended version)' tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 25 year: '2023' ... --- _id: '14920' abstract: - lang: eng text: "We consider fixpoint algorithms for two-player games on graphs with $\\omega$-regular winning conditions, where the environment is constrained by a strong transition fairness assumption. Strong transition fairness is a widely occurring special case of strong fairness, which requires that any execution is strongly fair with respect to a specified set of live edges: whenever the\r\nsource vertex of a live edge is visited infinitely often along a play, the edge itself is traversed infinitely often along the play as well. We show that, surprisingly, strong transition fairness retains the algorithmic characteristics of the fixpoint algorithms for $\\omega$-regular games -- the new algorithms have the same alternation depth as the classical algorithms but invoke a new type of predecessor operator. For Rabin games with $k$ pairs, the complexity of the new algorithm is $O(n^{k+2}k!)$ symbolic steps, which is independent of the number of live edges in the strong transition fairness assumption. Further, we show that GR(1) specifications with strong transition fairness assumptions can be solved with a 3-nested fixpoint algorithm, same as the usual algorithm. In contrast, strong fairness necessarily requires increasing the alternation depth depending on the number of fairness assumptions. We get symbolic algorithms for (generalized) Rabin, parity and GR(1) objectives under strong transition fairness assumptions as well as a direct symbolic algorithm for qualitative winning in stochastic\r\n$\\omega$-regular games that runs in $O(n^{k+2}k!)$ symbolic steps, improving the state of the art. Finally, we have implemented a BDD-based synthesis engine based on our algorithm. We show on a set of synthetic and real benchmarks that our algorithm is scalable, parallelizable, and outperforms previous algorithms by orders of magnitude." acknowledgement: A previous version of this paper has appeared in TACAS 2022. Authors ordered alphabetically. T. Banerjee was interning with MPI-SWS when this research was conducted. R. Majumdar and A.-K. Schmuck are partially supported by DFG project 389792660 TRR 248–CPEC. A.-K. Schmuck is additionally funded through DFG project (SCHM 3541/1-1). K. Mallik is supported by the ERC project ERC-2020-AdG 101020093. article_number: '4' article_processing_charge: Yes article_type: original author: - first_name: Tamajit full_name: Banerjee, Tamajit last_name: Banerjee - first_name: Rupak full_name: Majumdar, Rupak last_name: Majumdar - first_name: Kaushik full_name: Mallik, Kaushik id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598 last_name: Mallik orcid: 0000-0001-9864-7475 - first_name: Anne-Kathrin full_name: Schmuck, Anne-Kathrin last_name: Schmuck - first_name: Sadegh full_name: Soudjani, Sadegh last_name: Soudjani citation: ama: Banerjee T, Majumdar R, Mallik K, Schmuck A-K, Soudjani S. Fast symbolic algorithms for mega-regular games under strong transition fairness. TheoretiCS. 2023;2. doi:10.46298/theoretics.23.4 apa: Banerjee, T., Majumdar, R., Mallik, K., Schmuck, A.-K., & Soudjani, S. (2023). Fast symbolic algorithms for mega-regular games under strong transition fairness. TheoretiCS. EPI Sciences. https://doi.org/10.46298/theoretics.23.4 chicago: Banerjee, Tamajit, Rupak Majumdar, Kaushik Mallik, Anne-Kathrin Schmuck, and Sadegh Soudjani. “Fast Symbolic Algorithms for Mega-Regular Games under Strong Transition Fairness.” TheoretiCS. EPI Sciences, 2023. https://doi.org/10.46298/theoretics.23.4. ieee: T. Banerjee, R. Majumdar, K. Mallik, A.-K. Schmuck, and S. Soudjani, “Fast symbolic algorithms for mega-regular games under strong transition fairness,” TheoretiCS, vol. 2. EPI Sciences, 2023. ista: Banerjee T, Majumdar R, Mallik K, Schmuck A-K, Soudjani S. 2023. Fast symbolic algorithms for mega-regular games under strong transition fairness. TheoretiCS. 2, 4. mla: Banerjee, Tamajit, et al. “Fast Symbolic Algorithms for Mega-Regular Games under Strong Transition Fairness.” TheoretiCS, vol. 2, 4, EPI Sciences, 2023, doi:10.46298/theoretics.23.4. short: T. Banerjee, R. Majumdar, K. Mallik, A.-K. Schmuck, S. Soudjani, TheoretiCS 2 (2023). date_created: 2024-01-31T13:40:49Z date_published: 2023-02-24T00:00:00Z date_updated: 2024-02-05T10:21:51Z day: '24' ddc: - '000' department: - _id: ToHe doi: 10.46298/theoretics.23.4 ec_funded: 1 external_id: arxiv: - '2202.07480' file: - access_level: open_access checksum: 2972d531122a6f15727b396110fb3f5c content_type: application/pdf creator: dernst date_created: 2024-02-05T10:19:35Z date_updated: 2024-02-05T10:19:35Z file_id: '14940' file_name: 2023_TheoretiCS_Banerjee.pdf file_size: 917076 relation: main_file success: 1 file_date_updated: 2024-02-05T10:19:35Z has_accepted_license: '1' intvolume: ' 2' language: - iso: eng month: '02' oa: 1 oa_version: Published Version project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: TheoretiCS publication_identifier: issn: - 2751-4838 publication_status: published publisher: EPI Sciences quality_controlled: '1' status: public title: Fast symbolic algorithms for mega-regular games under strong transition fairness tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 2 year: '2023' ... --- _id: '14411' abstract: - lang: eng text: "Partially specified Boolean networks (PSBNs) represent a promising framework for the qualitative modelling of biological systems in which the logic of interactions is not completely known. Phenotype control aims to stabilise the network in states exhibiting specific traits.\r\nIn this paper, we define the phenotype control problem in the context of asynchronous PSBNs and propose a novel semi-symbolic algorithm for solving this problem with permanent variable perturbations." acknowledgement: This work was supported by the Czech Foundation grant No. GA22-10845S, Grant Agency of Masaryk University grant No. MUNI/G/1771/2020, and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 101034413. alternative_title: - LNBI article_processing_charge: No author: - first_name: Nikola full_name: Beneš, Nikola last_name: Beneš - first_name: Luboš full_name: Brim, Luboš last_name: Brim - first_name: Samuel full_name: Pastva, Samuel id: 07c5ea74-f61c-11ec-a664-aa7c5d957b2b last_name: Pastva orcid: 0000-0003-1993-0331 - first_name: David full_name: Šafránek, David last_name: Šafránek - first_name: Eva full_name: Šmijáková, Eva last_name: Šmijáková citation: ama: 'Beneš N, Brim L, Pastva S, Šafránek D, Šmijáková E. Phenotype control of partially specified boolean networks. In: 21st International Conference on Computational Methods in Systems Biology. Vol 14137. Springer Nature; 2023:18-35. doi:10.1007/978-3-031-42697-1_2' apa: 'Beneš, N., Brim, L., Pastva, S., Šafránek, D., & Šmijáková, E. (2023). Phenotype control of partially specified boolean networks. In 21st International Conference on Computational Methods in Systems Biology (Vol. 14137, pp. 18–35). Luxembourg City, Luxembourg: Springer Nature. https://doi.org/10.1007/978-3-031-42697-1_2' chicago: Beneš, Nikola, Luboš Brim, Samuel Pastva, David Šafránek, and Eva Šmijáková. “Phenotype Control of Partially Specified Boolean Networks.” In 21st International Conference on Computational Methods in Systems Biology, 14137:18–35. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-42697-1_2. ieee: N. Beneš, L. Brim, S. Pastva, D. Šafránek, and E. Šmijáková, “Phenotype control of partially specified boolean networks,” in 21st International Conference on Computational Methods in Systems Biology, Luxembourg City, Luxembourg, 2023, vol. 14137, pp. 18–35. ista: 'Beneš N, Brim L, Pastva S, Šafránek D, Šmijáková E. 2023. Phenotype control of partially specified boolean networks. 21st International Conference on Computational Methods in Systems Biology. CMSB: Computational Methods in Systems Biology, LNBI, vol. 14137, 18–35.' mla: Beneš, Nikola, et al. “Phenotype Control of Partially Specified Boolean Networks.” 21st International Conference on Computational Methods in Systems Biology, vol. 14137, Springer Nature, 2023, pp. 18–35, doi:10.1007/978-3-031-42697-1_2. short: N. Beneš, L. Brim, S. Pastva, D. Šafránek, E. Šmijáková, in:, 21st International Conference on Computational Methods in Systems Biology, Springer Nature, 2023, pp. 18–35. conference: end_date: 2023-09-15 location: Luxembourg City, Luxembourg name: 'CMSB: Computational Methods in Systems Biology' start_date: 2023-09-13 date_created: 2023-10-08T22:01:18Z date_published: 2023-09-09T00:00:00Z date_updated: 2024-02-20T09:02:04Z day: '09' ddc: - '000' department: - _id: ToHe doi: 10.1007/978-3-031-42697-1_2 ec_funded: 1 file: - access_level: open_access checksum: 6f71bdaedb770b52380222fd9f4d7937 content_type: application/pdf creator: spastva date_created: 2024-02-16T08:26:32Z date_updated: 2024-02-16T08:26:32Z file_id: '14997' file_name: cmsb2023.pdf file_size: 691582 relation: main_file success: 1 file_date_updated: 2024-02-16T08:26:32Z has_accepted_license: '1' intvolume: ' 14137' language: - iso: eng month: '09' oa: 1 oa_version: Submitted Version page: 18-35 project: - _id: fc2ed2f7-9c52-11eb-aca3-c01059dda49c call_identifier: H2020 grant_number: '101034413' name: 'IST-BRIDGE: International postdoctoral program' publication: 21st International Conference on Computational Methods in Systems Biology publication_identifier: eissn: - 1611-3349 isbn: - '9783031426964' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Phenotype control of partially specified boolean networks tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 14137 year: '2023' ... --- _id: '14758' abstract: - lang: eng text: 'We present a flexible and efficient toolchain to symbolically solve (standard) Rabin games, fair-adversarial Rabin games, and 2 1/2 license type-player Rabin games. To our best knowledge, our tools are the first ones to be able to solve these problems. Furthermore, using these flexible game solvers as a back-end, we implemented a tool for computing correct-by-construction controllers for stochastic dynamical systems under LTL specifications. Our implementations use the recent theoretical result that all of these games can be solved using the same symbolic fixpoint algorithm but utilizing different, domain specific calculations of the involved predecessor operators. The main feature of our toolchain is the utilization of two programming abstractions: one to separate the symbolic fixpoint computations from the predecessor calculations, and another one to allow the integration of different BDD libraries as back-ends. In particular, we employ a multi-threaded execution of the fixpoint algorithm by using the multi-threaded BDD library Sylvan, which leads to enormous computational savings.' acknowledgement: 'Authors ordered alphabetically. R. Majumdar and A.-K. Schmuck are partially supported by DFG project 389792660 TRR 248-CPEC. A.-K. Schmuck is additionally funded through DFG project (SCHM 3541/1-1). K. Mallik is supported by the ERC project ERC-2020-AdG 101020093. M. Rychlicki is supported by the EPSRC project EP/V00252X/1. S. Soudjani is supported by the following projects: EPSRC EP/V043676/1, EIC 101070802, and ERC 101089047.' alternative_title: - LNCS article_processing_charge: Yes (in subscription journal) author: - first_name: Rupak full_name: Majumdar, Rupak last_name: Majumdar - first_name: Kaushik full_name: Mallik, Kaushik id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598 last_name: Mallik orcid: 0000-0001-9864-7475 - first_name: Mateusz full_name: Rychlicki, Mateusz last_name: Rychlicki - first_name: Anne-Kathrin full_name: Schmuck, Anne-Kathrin last_name: Schmuck - first_name: Sadegh full_name: Soudjani, Sadegh last_name: Soudjani citation: ama: 'Majumdar R, Mallik K, Rychlicki M, Schmuck A-K, Soudjani S. A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties. In: 35th International Conference on Computer Aided Verification. Vol 13966. Springer Nature; 2023:3-15. doi:10.1007/978-3-031-37709-9_1' apa: 'Majumdar, R., Mallik, K., Rychlicki, M., Schmuck, A.-K., & Soudjani, S. (2023). A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties. In 35th International Conference on Computer Aided Verification (Vol. 13966, pp. 3–15). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-37709-9_1' chicago: Majumdar, Rupak, Kaushik Mallik, Mateusz Rychlicki, Anne-Kathrin Schmuck, and Sadegh Soudjani. “A Flexible Toolchain for Symbolic Rabin Games under Fair and Stochastic Uncertainties.” In 35th International Conference on Computer Aided Verification, 13966:3–15. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-37709-9_1. ieee: R. Majumdar, K. Mallik, M. Rychlicki, A.-K. Schmuck, and S. Soudjani, “A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties,” in 35th International Conference on Computer Aided Verification, Paris, France, 2023, vol. 13966, pp. 3–15. ista: 'Majumdar R, Mallik K, Rychlicki M, Schmuck A-K, Soudjani S. 2023. A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties. 35th International Conference on Computer Aided Verification. CAV: Computer Aided Verification, LNCS, vol. 13966, 3–15.' mla: Majumdar, Rupak, et al. “A Flexible Toolchain for Symbolic Rabin Games under Fair and Stochastic Uncertainties.” 35th International Conference on Computer Aided Verification, vol. 13966, Springer Nature, 2023, pp. 3–15, doi:10.1007/978-3-031-37709-9_1. short: R. Majumdar, K. Mallik, M. Rychlicki, A.-K. Schmuck, S. Soudjani, in:, 35th International Conference on Computer Aided Verification, Springer Nature, 2023, pp. 3–15. conference: end_date: 2023-07-22 location: Paris, France name: 'CAV: Computer Aided Verification' start_date: 2023-07-17 date_created: 2024-01-08T13:18:00Z date_published: 2023-07-16T00:00:00Z date_updated: 2024-02-27T07:39:51Z day: '16' ddc: - '000' department: - _id: ToHe doi: 10.1007/978-3-031-37709-9_1 ec_funded: 1 file: - access_level: open_access checksum: 1a361d83db0244fd32c03b544c294b5a content_type: application/pdf creator: dernst date_created: 2024-01-09T10:01:07Z date_updated: 2024-01-09T10:01:07Z file_id: '14765' file_name: 2023_LNCSCAV_Majumdar.pdf file_size: 405147 relation: main_file success: 1 file_date_updated: 2024-01-09T10:01:07Z has_accepted_license: '1' intvolume: ' 13966' language: - iso: eng month: '07' oa: 1 oa_version: Published Version page: 3-15 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 35th International Conference on Computer Aided Verification publication_identifier: eisbn: - '9783031377099' eissn: - 1611-3349 isbn: - '9783031377082' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: record: - id: '14994' relation: research_data status: public scopus_import: '1' status: public title: A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 13966 year: '2023' ... --- _id: '14994' abstract: - lang: eng text: This resource contains the artifacts for reproducing the experimental results presented in the paper titled "A Flexible Toolchain for Symbolic Rabin Games under Fair and Stochastic Uncertainties" that has been submitted in CAV 2023. article_processing_charge: No author: - first_name: Rupak full_name: Majumdar, Rupak last_name: Majumdar - first_name: Kaushik full_name: Mallik, Kaushik id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598 last_name: Mallik orcid: 0000-0001-9864-7475 - first_name: Mateusz full_name: Rychlicki, Mateusz last_name: Rychlicki - first_name: Anne-Kathrin full_name: Schmuck, Anne-Kathrin last_name: Schmuck - first_name: Sadegh full_name: Soudjani, Sadegh last_name: Soudjani citation: ama: Majumdar R, Mallik K, Rychlicki M, Schmuck A-K, Soudjani S. A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties. 2023. doi:10.5281/ZENODO.7877790 apa: Majumdar, R., Mallik, K., Rychlicki, M., Schmuck, A.-K., & Soudjani, S. (2023). A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties. Zenodo. https://doi.org/10.5281/ZENODO.7877790 chicago: Majumdar, Rupak, Kaushik Mallik, Mateusz Rychlicki, Anne-Kathrin Schmuck, and Sadegh Soudjani. “A Flexible Toolchain for Symbolic Rabin Games under Fair and Stochastic Uncertainties.” Zenodo, 2023. https://doi.org/10.5281/ZENODO.7877790. ieee: R. Majumdar, K. Mallik, M. Rychlicki, A.-K. Schmuck, and S. Soudjani, “A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties.” Zenodo, 2023. ista: Majumdar R, Mallik K, Rychlicki M, Schmuck A-K, Soudjani S. 2023. A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties, Zenodo, 10.5281/ZENODO.7877790. mla: Majumdar, Rupak, et al. A Flexible Toolchain for Symbolic Rabin Games under Fair and Stochastic Uncertainties. Zenodo, 2023, doi:10.5281/ZENODO.7877790. short: R. Majumdar, K. Mallik, M. Rychlicki, A.-K. Schmuck, S. Soudjani, (2023). date_created: 2024-02-14T15:13:00Z date_published: 2023-04-28T00:00:00Z date_updated: 2024-02-27T07:39:51Z day: '28' ddc: - '000' department: - _id: ToHe doi: 10.5281/ZENODO.7877790 has_accepted_license: '1' main_file_link: - open_access: '1' url: https://doi.org/10.5281/zenodo.7877790 month: '04' oa: 1 oa_version: Published Version publisher: Zenodo related_material: record: - id: '14758' relation: used_in_publication status: public status: public title: A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: research_data_reference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2023' ... --- _id: '15023' abstract: - lang: eng text: Reinforcement learning has shown promising results in learning neural network policies for complicated control tasks. However, the lack of formal guarantees about the behavior of such policies remains an impediment to their deployment. We propose a novel method for learning a composition of neural network policies in stochastic environments, along with a formal certificate which guarantees that a specification over the policy's behavior is satisfied with the desired probability. Unlike prior work on verifiable RL, our approach leverages the compositional nature of logical specifications provided in SpectRL, to learn over graphs of probabilistic reach-avoid specifications. The formal guarantees are provided by learning neural network policies together with reach-avoid supermartingales (RASM) for the graph’s sub-tasks and then composing them into a global policy. We also derive a tighter lower bound compared to previous work on the probability of reach-avoidance implied by a RASM, which is required to find a compositional policy with an acceptable probabilistic threshold for complex tasks with multiple edge policies. We implement a prototype of our approach and evaluate it on a Stochastic Nine Rooms environment. acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093 (VAMOS) and the ERC-2020-\r\nCoG 863818 (FoRM-SMArt)." article_processing_charge: No author: - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Abhinav full_name: Verma, Abhinav id: a235593c-d7fa-11eb-a0c5-b22ca3c66ee6 last_name: Verma - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: 'Zikelic D, Lechner M, Verma A, Chatterjee K, Henzinger TA. Compositional policy learning in stochastic control systems with formal guarantees. In: 37th Conference on Neural Information Processing Systems. ; 2023.' apa: Zikelic, D., Lechner, M., Verma, A., Chatterjee, K., & Henzinger, T. A. (2023). Compositional policy learning in stochastic control systems with formal guarantees. In 37th Conference on Neural Information Processing Systems. New Orleans, LO, United States. chicago: Zikelic, Dorde, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee, and Thomas A Henzinger. “Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees.” In 37th Conference on Neural Information Processing Systems, 2023. ieee: D. Zikelic, M. Lechner, A. Verma, K. Chatterjee, and T. A. Henzinger, “Compositional policy learning in stochastic control systems with formal guarantees,” in 37th Conference on Neural Information Processing Systems, New Orleans, LO, United States, 2023. ista: 'Zikelic D, Lechner M, Verma A, Chatterjee K, Henzinger TA. 2023. Compositional policy learning in stochastic control systems with formal guarantees. 37th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems.' mla: Zikelic, Dorde, et al. “Compositional Policy Learning in Stochastic Control Systems with Formal Guarantees.” 37th Conference on Neural Information Processing Systems, 2023. short: D. Zikelic, M. Lechner, A. Verma, K. Chatterjee, T.A. Henzinger, in:, 37th Conference on Neural Information Processing Systems, 2023. conference: end_date: 2023-12-16 location: New Orleans, LO, United States name: 'NeurIPS: Neural Information Processing Systems' start_date: 2023-12-10 date_created: 2024-02-25T09:23:24Z date_published: 2023-12-15T00:00:00Z date_updated: 2024-02-28T12:20:11Z day: '15' department: - _id: ToHe - _id: KrCh ec_funded: 1 external_id: arxiv: - '2312.01456' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2312.01456 month: '12' oa: 1 oa_version: Preprint project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 37th Conference on Neural Information Processing Systems publication_status: epub_ahead quality_controlled: '1' status: public title: Compositional policy learning in stochastic control systems with formal guarantees type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2023' ... --- _id: '14076' abstract: - lang: eng text: Hyperproperties are properties that relate multiple execution traces. Previous work on monitoring hyperproperties focused on synchronous hyperproperties, usually specified in HyperLTL. When monitoring synchronous hyperproperties, all traces are assumed to proceed at the same speed. We introduce (multi-trace) prefix transducers and show how to use them for monitoring synchronous as well as, for the first time, asynchronous hyperproperties. Prefix transducers map multiple input traces into one or more output traces by incrementally matching prefixes of the input traces against expressions similar to regular expressions. The prefixes of different traces which are consumed by a single matching step of the monitor may have different lengths. The deterministic and executable nature of prefix transducers makes them more suitable as an intermediate formalism for runtime verification than logical specifications, which tend to be highly non-deterministic, especially in the case of asynchronous hyperproperties. We report on a set of experiments about monitoring asynchronous version of observational determinism. acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093. The authors would like to thank Ana Oliveira da Costa for commenting on a draft of the paper. alternative_title: - LNCS article_processing_charge: Yes (in subscription journal) author: - first_name: Marek full_name: Chalupa, Marek id: 87e34708-d6c6-11ec-9f5b-9391e7be2463 last_name: Chalupa - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: 'Chalupa M, Henzinger TA. Monitoring hyperproperties with prefix transducers. In: 23nd International Conference on Runtime Verification. Vol 14245. Springer Nature; 2023:168-190. doi:10.1007/978-3-031-44267-4_9' apa: 'Chalupa, M., & Henzinger, T. A. (2023). Monitoring hyperproperties with prefix transducers. In 23nd International Conference on Runtime Verification (Vol. 14245, pp. 168–190). Thessaloniki, Greek: Springer Nature. https://doi.org/10.1007/978-3-031-44267-4_9' chicago: Chalupa, Marek, and Thomas A Henzinger. “Monitoring Hyperproperties with Prefix Transducers.” In 23nd International Conference on Runtime Verification, 14245:168–90. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-44267-4_9. ieee: M. Chalupa and T. A. Henzinger, “Monitoring hyperproperties with prefix transducers,” in 23nd International Conference on Runtime Verification, Thessaloniki, Greek, 2023, vol. 14245, pp. 168–190. ista: 'Chalupa M, Henzinger TA. 2023. Monitoring hyperproperties with prefix transducers. 23nd International Conference on Runtime Verification. RV: Conference on Runtime Verification, LNCS, vol. 14245, 168–190.' mla: Chalupa, Marek, and Thomas A. Henzinger. “Monitoring Hyperproperties with Prefix Transducers.” 23nd International Conference on Runtime Verification, vol. 14245, Springer Nature, 2023, pp. 168–90, doi:10.1007/978-3-031-44267-4_9. short: M. Chalupa, T.A. Henzinger, in:, 23nd International Conference on Runtime Verification, Springer Nature, 2023, pp. 168–190. conference: end_date: 2023-10-07 location: Thessaloniki, Greek name: 'RV: Conference on Runtime Verification' start_date: 2023-10-04 date_created: 2023-08-16T20:46:08Z date_published: 2023-10-01T00:00:00Z date_updated: 2024-02-28T12:33:08Z day: '01' ddc: - '000' department: - _id: ToHe doi: 10.1007/978-3-031-44267-4_9 ec_funded: 1 file: - access_level: open_access checksum: ee33bd6f1a26f4dae7a8192584869fd8 content_type: application/pdf creator: dernst date_created: 2023-10-16T07:15:11Z date_updated: 2023-10-16T07:15:11Z file_id: '14430' file_name: 2023_LNCS_RV_Chalupa.pdf file_size: 867256 relation: main_file success: 1 file_date_updated: 2023-10-16T07:15:11Z has_accepted_license: '1' intvolume: ' 14245' language: - iso: eng month: '10' oa: 1 oa_version: Published Version page: 168-190 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 23nd International Conference on Runtime Verification publication_identifier: eisbn: - 978-3-031-44267-4 isbn: - 978-3-031-44266-7 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: record: - id: '15035' relation: research_data status: public status: public title: Monitoring hyperproperties with prefix transducers tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 14245 year: '2023' ... --- _id: '15035' abstract: - lang: eng text: "This artifact aims to reproduce experiments from the paper Monitoring Hyperproperties With Prefix Transducers accepted at RV'23, and give further pointers to implementation of prefix transducers.\r\nIt has two parts: a pre-compiled docker image and sources that one can use to compile (locally or in docker) the software and run the experiments." article_processing_charge: No author: - first_name: Marek full_name: Chalupa, Marek id: 87e34708-d6c6-11ec-9f5b-9391e7be2463 last_name: Chalupa - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: Chalupa M, Henzinger TA. Monitoring hyperproperties with prefix transducers. 2023. doi:10.5281/ZENODO.8191723 apa: Chalupa, M., & Henzinger, T. A. (2023). Monitoring hyperproperties with prefix transducers. Zenodo. https://doi.org/10.5281/ZENODO.8191723 chicago: Chalupa, Marek, and Thomas A Henzinger. “Monitoring Hyperproperties with Prefix Transducers.” Zenodo, 2023. https://doi.org/10.5281/ZENODO.8191723. ieee: M. Chalupa and T. A. Henzinger, “Monitoring hyperproperties with prefix transducers.” Zenodo, 2023. ista: Chalupa M, Henzinger TA. 2023. Monitoring hyperproperties with prefix transducers, Zenodo, 10.5281/ZENODO.8191723. mla: Chalupa, Marek, and Thomas A. Henzinger. Monitoring Hyperproperties with Prefix Transducers. Zenodo, 2023, doi:10.5281/ZENODO.8191723. short: M. Chalupa, T.A. Henzinger, (2023). date_created: 2024-02-28T07:34:34Z date_published: 2023-07-28T00:00:00Z date_updated: 2024-02-28T12:33:09Z day: '28' ddc: - '000' department: - _id: ToHe doi: 10.5281/ZENODO.8191723 ec_funded: 1 has_accepted_license: '1' main_file_link: - open_access: '1' url: https://doi.org/10.5281/zenodo.8191722 month: '07' oa: 1 oa_version: Published Version project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publisher: Zenodo related_material: record: - id: '14076' relation: used_in_publication status: public status: public title: Monitoring hyperproperties with prefix transducers tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: research_data_reference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2023' ... --- _id: '10774' abstract: - lang: eng text: We study the problem of specifying sequential information-flow properties of systems. Information-flow properties are hyperproperties, as they compare different traces of a system. Sequential information-flow properties can express changes, over time, in the information-flow constraints. For example, information-flow constraints during an initialization phase of a system may be different from information-flow constraints that are required during the operation phase. We formalize several variants of interpreting sequential information-flow constraints, which arise from different assumptions about what can be observed of the system. For this purpose, we introduce a first-order logic, called Hypertrace Logic, with both trace and time quantifiers for specifying linear-time hyperproperties. We prove that HyperLTL, which corresponds to a fragment of Hypertrace Logic with restricted quantifier prefixes, cannot specify the majority of the studied variants of sequential information flow, including all variants in which the transition between sequential phases (such as initialization and operation) happens asynchronously. Our results rely on new equivalences between sets of traces that cannot be distinguished by certain classes of formulas from Hypertrace Logic. This presents a new approach to proving inexpressiveness results for HyperLTL. acknowledgement: This work was funded in part by the Wittgenstein Award Z211-N23 of the Austrian Science Fund (FWF) and by the FWF project W1255-N23. alternative_title: - LNCS article_processing_charge: No author: - first_name: Ezio full_name: Bartocci, Ezio last_name: Bartocci - first_name: Thomas full_name: Ferrere, Thomas id: 40960E6E-F248-11E8-B48F-1D18A9856A87 last_name: Ferrere orcid: 0000-0001-5199-3143 - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Dejan full_name: Nickovic, Dejan id: 41BCEE5C-F248-11E8-B48F-1D18A9856A87 last_name: Nickovic - first_name: Ana Oliveira full_name: Da Costa, Ana Oliveira last_name: Da Costa citation: ama: 'Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. Flavors of sequential information flow. In: Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 13182. Springer Nature; 2022:1-19. doi:10.1007/978-3-030-94583-1_1' apa: 'Bartocci, E., Ferrere, T., Henzinger, T. A., Nickovic, D., & Da Costa, A. O. (2022). Flavors of sequential information flow. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13182, pp. 1–19). Philadelphia, PA, United States: Springer Nature. https://doi.org/10.1007/978-3-030-94583-1_1' chicago: Bartocci, Ezio, Thomas Ferrere, Thomas A Henzinger, Dejan Nickovic, and Ana Oliveira Da Costa. “Flavors of Sequential Information Flow.” In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 13182:1–19. Springer Nature, 2022. https://doi.org/10.1007/978-3-030-94583-1_1. ieee: E. Bartocci, T. Ferrere, T. A. Henzinger, D. Nickovic, and A. O. Da Costa, “Flavors of sequential information flow,” in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Philadelphia, PA, United States, 2022, vol. 13182, pp. 1–19. ista: 'Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. 2022. Flavors of sequential information flow. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). VMCAI: Verifcation, Model Checking, and Abstract Interpretation, LNCS, vol. 13182, 1–19.' mla: Bartocci, Ezio, et al. “Flavors of Sequential Information Flow.” Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 13182, Springer Nature, 2022, pp. 1–19, doi:10.1007/978-3-030-94583-1_1. short: E. Bartocci, T. Ferrere, T.A. Henzinger, D. Nickovic, A.O. Da Costa, in:, Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Nature, 2022, pp. 1–19. conference: end_date: 2022-01-18 location: Philadelphia, PA, United States name: 'VMCAI: Verifcation, Model Checking, and Abstract Interpretation' start_date: 2022-01-16 date_created: 2022-02-20T23:01:34Z date_published: 2022-01-14T00:00:00Z date_updated: 2022-08-05T09:02:56Z day: '14' department: - _id: ToHe doi: 10.1007/978-3-030-94583-1_1 external_id: arxiv: - '2105.02013' intvolume: ' 13182' language: - iso: eng main_file_link: - open_access: '1' url: ' https://doi.org/10.48550/arXiv.2105.02013' month: '01' oa: 1 oa_version: Preprint page: 1-19 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) publication_identifier: eissn: - '16113349' isbn: - '9783030945824' issn: - '03029743' publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Flavors of sequential information flow type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 13182 year: '2022' ... --- _id: '12010' abstract: - lang: eng text: World models learn behaviors in a latent imagination space to enhance the sample-efficiency of deep reinforcement learning (RL) algorithms. While learning world models for high-dimensional observations (e.g., pixel inputs) has become practicable on standard RL benchmarks and some games, their effectiveness in real-world robotics applications has not been explored. In this paper, we investigate how such agents generalize to real-world autonomous vehicle control tasks, where advanced model-free deep RL algorithms fail. In particular, we set up a series of time-lap tasks for an F1TENTH racing robot, equipped with a high-dimensional LiDAR sensor, on a set of test tracks with a gradual increase in their complexity. In this continuous-control setting, we show that model-based agents capable of learning in imagination substantially outperform model-free agents with respect to performance, sample efficiency, successful task completion, and generalization. Moreover, we show that the generalization ability of model-based agents strongly depends on the choice of their observation model. We provide extensive empirical evidence for the effectiveness of world models provided with long enough memory horizons in sim2real tasks. acknowledgement: L.B. was supported by the Doctoral College Resilient Embedded Systems. M.L. was supported in part by the ERC2020-AdG 101020093 and the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). R.H. and D.R. were supported by The Boeing Company and the Office of Naval Research (ONR) Grant N00014-18-1-2830. R.G. was partially supported by the Horizon-2020 ECSEL Project grant No. 783163 (iDev40) and A.B. by FFG Project ADEX. article_processing_charge: No author: - first_name: Axel full_name: Brunnbauer, Axel last_name: Brunnbauer - first_name: Luigi full_name: Berducci, Luigi last_name: Berducci - first_name: Andreas full_name: Brandstatter, Andreas last_name: Brandstatter - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Daniela full_name: Rus, Daniela last_name: Rus - first_name: Radu full_name: Grosu, Radu last_name: Grosu citation: ama: 'Brunnbauer A, Berducci L, Brandstatter A, et al. Latent imagination facilitates zero-shot transfer in autonomous racing. In: 2022 International Conference on Robotics and Automation. IEEE; 2022:7513-7520. doi:10.1109/ICRA46639.2022.9811650' apa: 'Brunnbauer, A., Berducci, L., Brandstatter, A., Lechner, M., Hasani, R., Rus, D., & Grosu, R. (2022). Latent imagination facilitates zero-shot transfer in autonomous racing. In 2022 International Conference on Robotics and Automation (pp. 7513–7520). Philadelphia, PA, United States: IEEE. https://doi.org/10.1109/ICRA46639.2022.9811650' chicago: Brunnbauer, Axel, Luigi Berducci, Andreas Brandstatter, Mathias Lechner, Ramin Hasani, Daniela Rus, and Radu Grosu. “Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing.” In 2022 International Conference on Robotics and Automation, 7513–20. IEEE, 2022. https://doi.org/10.1109/ICRA46639.2022.9811650. ieee: A. Brunnbauer et al., “Latent imagination facilitates zero-shot transfer in autonomous racing,” in 2022 International Conference on Robotics and Automation, Philadelphia, PA, United States, 2022, pp. 7513–7520. ista: 'Brunnbauer A, Berducci L, Brandstatter A, Lechner M, Hasani R, Rus D, Grosu R. 2022. Latent imagination facilitates zero-shot transfer in autonomous racing. 2022 International Conference on Robotics and Automation. ICRA: International Conference on Robotics and Automation, 7513–7520.' mla: Brunnbauer, Axel, et al. “Latent Imagination Facilitates Zero-Shot Transfer in Autonomous Racing.” 2022 International Conference on Robotics and Automation, IEEE, 2022, pp. 7513–20, doi:10.1109/ICRA46639.2022.9811650. short: A. Brunnbauer, L. Berducci, A. Brandstatter, M. Lechner, R. Hasani, D. Rus, R. Grosu, in:, 2022 International Conference on Robotics and Automation, IEEE, 2022, pp. 7513–7520. conference: end_date: 2022-05-27 location: Philadelphia, PA, United States name: 'ICRA: International Conference on Robotics and Automation' start_date: 2022-05-23 date_created: 2022-09-04T22:02:02Z date_published: 2022-07-12T00:00:00Z date_updated: 2022-09-05T08:46:12Z day: '12' department: - _id: ToHe doi: 10.1109/ICRA46639.2022.9811650 ec_funded: 1 external_id: arxiv: - '2103.04909' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2103.04909 month: '07' oa: 1 oa_version: Preprint page: 7513-7520 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: 2022 International Conference on Robotics and Automation publication_identifier: isbn: - '9781728196817' issn: - 1050-4729 publication_status: published publisher: IEEE quality_controlled: '1' scopus_import: '1' status: public title: Latent imagination facilitates zero-shot transfer in autonomous racing type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '12171' abstract: - lang: eng text: 'We propose an algorithmic approach for synthesizing linear hybrid automata from time-series data. Unlike existing approaches, our approach provides a whole family of models with the same discrete structure but different dynamics. Each model in the family is guaranteed to capture the input data up to a precision error ε, in the following sense: For each time series, the model contains an execution that is ε-close to the data points. Our construction allows to effectively choose a model from this family with minimal precision error ε. We demonstrate the algorithm’s efficiency and its ability to find precise models in two case studies.' acknowledgement: This work was supported in part by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement no. 847635, by the ERC-2020-AdG 101020093, by DIREC - Digital Research Centre Denmark, and by the Villum Investigator Grant S4OS. alternative_title: - LNCS article_processing_charge: No author: - first_name: Miriam full_name: Garcia Soto, Miriam id: 4B3207F6-F248-11E8-B48F-1D18A9856A87 last_name: Garcia Soto orcid: 0000-0003-2936-5719 - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Christian full_name: Schilling, Christian id: 3A2F4DCE-F248-11E8-B48F-1D18A9856A87 last_name: Schilling orcid: 0000-0003-3658-1065 citation: ama: 'Garcia Soto M, Henzinger TA, Schilling C. Synthesis of parametric hybrid automata from time series. In: 20th International Symposium on Automated Technology for Verification and Analysis. Vol 13505. Springer Nature; 2022:337-353. doi:10.1007/978-3-031-19992-9_22' apa: 'Garcia Soto, M., Henzinger, T. A., & Schilling, C. (2022). Synthesis of parametric hybrid automata from time series. In 20th International Symposium on Automated Technology for Verification and Analysis (Vol. 13505, pp. 337–353). Virtual: Springer Nature. https://doi.org/10.1007/978-3-031-19992-9_22' chicago: Garcia Soto, Miriam, Thomas A Henzinger, and Christian Schilling. “Synthesis of Parametric Hybrid Automata from Time Series.” In 20th International Symposium on Automated Technology for Verification and Analysis, 13505:337–53. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-19992-9_22. ieee: M. Garcia Soto, T. A. Henzinger, and C. Schilling, “Synthesis of parametric hybrid automata from time series,” in 20th International Symposium on Automated Technology for Verification and Analysis, Virtual, 2022, vol. 13505, pp. 337–353. ista: 'Garcia Soto M, Henzinger TA, Schilling C. 2022. Synthesis of parametric hybrid automata from time series. 20th International Symposium on Automated Technology for Verification and Analysis. ATVA: Automated Technology for Verification and Analysis, LNCS, vol. 13505, 337–353.' mla: Garcia Soto, Miriam, et al. “Synthesis of Parametric Hybrid Automata from Time Series.” 20th International Symposium on Automated Technology for Verification and Analysis, vol. 13505, Springer Nature, 2022, pp. 337–53, doi:10.1007/978-3-031-19992-9_22. short: M. Garcia Soto, T.A. Henzinger, C. Schilling, in:, 20th International Symposium on Automated Technology for Verification and Analysis, Springer Nature, 2022, pp. 337–353. conference: end_date: 2022-10-28 location: Virtual name: 'ATVA: Automated Technology for Verification and Analysis' start_date: 2022-10-25 date_created: 2023-01-12T12:11:16Z date_published: 2022-10-21T00:00:00Z date_updated: 2023-02-13T09:27:55Z day: '21' department: - _id: ToHe doi: 10.1007/978-3-031-19992-9_22 ec_funded: 1 external_id: arxiv: - '2208.06383' intvolume: ' 13505' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2208.06383 month: '10' oa: 1 oa_version: Preprint page: 337-353 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 20th International Symposium on Automated Technology for Verification and Analysis publication_identifier: eisbn: - '9783031199929' eissn: - 1611-3349 isbn: - '9783031199912' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Synthesis of parametric hybrid automata from time series type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 13505 year: '2022' ... --- _id: '12508' abstract: - lang: eng text: "We explore the notion of history-determinism in the context of timed automata (TA). History-deterministic automata are those in which nondeterminism can be resolved on the fly, based on the run constructed thus far. History-determinism is a robust property that admits different game-based characterisations, and history-deterministic specifications allow for game-based verification without an expensive determinization step.\r\nWe show yet another characterisation of history-determinism in terms of fair simulation, at the general level of labelled transition systems: a system is history-deterministic precisely if and only if it fairly simulates all language smaller systems.\r\nFor timed automata over infinite timed words it is known that universality is undecidable for Büchi TA. We show that for history-deterministic TA with arbitrary parity acceptance, timed universality, inclusion, and synthesis all remain decidable and are ExpTime-complete.\r\nFor the subclass of TA with safety or reachability acceptance, we show that checking whether such an automaton is history-deterministic is decidable (in ExpTime), and history-deterministic TA with safety acceptance are effectively determinizable without introducing new automata states." acknowledgement: "Thomas A. Henzinger: This work was supported in part by the ERC-2020-AdG 101020093.\r\nPatrick Totzke: acknowledges support from the EPSRC, project no. EP/V025848/1.\r\n" alternative_title: - LIPIcs article_processing_charge: No author: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Karoliina full_name: Lehtinen, Karoliina last_name: Lehtinen - first_name: Patrick full_name: Totzke, Patrick last_name: Totzke citation: ama: 'Henzinger TA, Lehtinen K, Totzke P. History-deterministic timed automata. In: 33rd International Conference on Concurrency Theory. Vol 243. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022:14:1-14:21. doi:10.4230/LIPIcs.CONCUR.2022.14' apa: 'Henzinger, T. A., Lehtinen, K., & Totzke, P. (2022). History-deterministic timed automata. In 33rd International Conference on Concurrency Theory (Vol. 243, p. 14:1-14:21). Warsaw, Poland: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2022.14' chicago: Henzinger, Thomas A, Karoliina Lehtinen, and Patrick Totzke. “History-Deterministic Timed Automata.” In 33rd International Conference on Concurrency Theory, 243:14:1-14:21. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.CONCUR.2022.14. ieee: T. A. Henzinger, K. Lehtinen, and P. Totzke, “History-deterministic timed automata,” in 33rd International Conference on Concurrency Theory, Warsaw, Poland, 2022, vol. 243, p. 14:1-14:21. ista: 'Henzinger TA, Lehtinen K, Totzke P. 2022. History-deterministic timed automata. 33rd International Conference on Concurrency Theory. CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 243, 14:1-14:21.' mla: Henzinger, Thomas A., et al. “History-Deterministic Timed Automata.” 33rd International Conference on Concurrency Theory, vol. 243, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, p. 14:1-14:21, doi:10.4230/LIPIcs.CONCUR.2022.14. short: T.A. Henzinger, K. Lehtinen, P. Totzke, in:, 33rd International Conference on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, p. 14:1-14:21. conference: end_date: 2022-09-16 location: Warsaw, Poland name: 'CONCUR: Conference on Concurrency Theory' start_date: 2022-09-13 date_created: 2023-02-05T17:24:23Z date_published: 2022-09-06T00:00:00Z date_updated: 2023-02-06T09:23:31Z day: '06' ddc: - '000' department: - _id: ToHe doi: 10.4230/LIPIcs.CONCUR.2022.14 ec_funded: 1 file: - access_level: open_access checksum: 9e97e15628f66b2ad77f535bb0327dee content_type: application/pdf creator: dernst date_created: 2023-02-06T09:21:09Z date_updated: 2023-02-06T09:21:09Z file_id: '12520' file_name: 2022_LIPICs_Henzinger2.pdf file_size: 717940 relation: main_file success: 1 file_date_updated: 2023-02-06T09:21:09Z has_accepted_license: '1' intvolume: ' 243' language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: 14:1-14:21 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 33rd International Conference on Concurrency Theory publication_identifier: isbn: - '9783959772464' issn: - 1868-8969 publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' scopus_import: '1' status: public title: History-deterministic timed automata tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 243 year: '2022' ... --- _id: '12509' abstract: - lang: eng text: A graph game is a two-player zero-sum game in which the players move a token throughout a graph to produce an infinite path, which determines the winner or payoff of the game. In bidding games, both players have budgets, and in each turn, we hold an "auction" (bidding) to determine which player moves the token. In this survey, we consider several bidding mechanisms and their effect on the properties of the game. Specifically, bidding games, and in particular bidding games of infinite duration, have an intriguing equivalence with random-turn games in which in each turn, the player who moves is chosen randomly. We summarize how minor changes in the bidding mechanism lead to unexpected differences in the equivalence with random-turn games. acknowledgement: "Guy Avni: Work partially supported by the Israel Science Foundation, ISF grant agreement\r\nno 1679/21.\r\nThomas A. Henzinger: This work was supported in part by the ERC-2020-AdG 101020093.\r\nWe would like to thank all our collaborators Milad Aghajohari, Ventsislav Chonev, Rasmus Ibsen-Jensen, Ismäel Jecker, Petr Novotný, Josef Tkadlec, and Ðorđe Žikelić; we hope the collaboration was as fun and meaningful for you as it was for us." article_processing_charge: No author: - first_name: Guy full_name: Avni, Guy id: 463C8BC2-F248-11E8-B48F-1D18A9856A87 last_name: Avni orcid: 0000-0001-5588-8287 - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: 'Avni G, Henzinger TA. An updated survey of bidding games on graphs. In: 47th International Symposium on Mathematical Foundations of Computer Science. Vol 241. Leibniz International Proceedings in Informatics (LIPIcs). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022:3:1-3:6. doi:10.4230/LIPIcs.MFCS.2022.3' apa: 'Avni, G., & Henzinger, T. A. (2022). An updated survey of bidding games on graphs. In 47th International Symposium on Mathematical Foundations of Computer Science (Vol. 241, p. 3:1-3:6). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.MFCS.2022.3' chicago: 'Avni, Guy, and Thomas A Henzinger. “An Updated Survey of Bidding Games on Graphs.” In 47th International Symposium on Mathematical Foundations of Computer Science, 241:3:1-3:6. Leibniz International Proceedings in Informatics (LIPIcs). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.MFCS.2022.3.' ieee: G. Avni and T. A. Henzinger, “An updated survey of bidding games on graphs,” in 47th International Symposium on Mathematical Foundations of Computer Science, Vienna, Austria, 2022, vol. 241, p. 3:1-3:6. ista: 'Avni G, Henzinger TA. 2022. An updated survey of bidding games on graphs. 47th International Symposium on Mathematical Foundations of Computer Science. MFCS: Symposium on Mathematical Foundations of Computer ScienceLeibniz International Proceedings in Informatics (LIPIcs) vol. 241, 3:1-3:6.' mla: Avni, Guy, and Thomas A. Henzinger. “An Updated Survey of Bidding Games on Graphs.” 47th International Symposium on Mathematical Foundations of Computer Science, vol. 241, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, p. 3:1-3:6, doi:10.4230/LIPIcs.MFCS.2022.3. short: G. Avni, T.A. Henzinger, in:, 47th International Symposium on Mathematical Foundations of Computer Science, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Dagstuhl, Germany, 2022, p. 3:1-3:6. conference: end_date: 2022-08-26 location: Vienna, Austria name: 'MFCS: Symposium on Mathematical Foundations of Computer Science' start_date: 2022-08-22 date_created: 2023-02-05T17:26:01Z date_published: 2022-08-22T00:00:00Z date_updated: 2023-02-06T09:16:54Z day: '22' ddc: - '000' department: - _id: ToHe doi: 10.4230/LIPIcs.MFCS.2022.3 ec_funded: 1 file: - access_level: open_access checksum: 1888ec9421622f9526fbec2de035f132 content_type: application/pdf creator: dernst date_created: 2023-02-06T09:13:04Z date_updated: 2023-02-06T09:13:04Z file_id: '12519' file_name: 2022_LIPICs_Avni.pdf file_size: 624586 relation: main_file success: 1 file_date_updated: 2023-02-06T09:13:04Z has_accepted_license: '1' intvolume: ' 241' language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: 3:1-3:6 place: Dagstuhl, Germany project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 47th International Symposium on Mathematical Foundations of Computer Science publication_identifier: isbn: - '9783959772563' issn: - 1868-8969 publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' scopus_import: '1' series_title: Leibniz International Proceedings in Informatics (LIPIcs) status: public title: An updated survey of bidding games on graphs tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 241 year: '2022' ... --- _id: '11366' abstract: - lang: eng text: "Adversarial training (i.e., training on adversarially perturbed input data) is a well-studied method for making neural networks robust to potential adversarial attacks during inference. However, the improved robustness does not\r\ncome for free but rather is accompanied by a decrease in overall model accuracy and performance. Recent work has shown that, in practical robot learning applications, the effects of adversarial training do not pose a fair trade-off\r\nbut inflict a net loss when measured in holistic robot performance. This work revisits the robustness-accuracy trade-off in robot learning by systematically analyzing if recent advances in robust training methods and theory in\r\nconjunction with adversarial robot learning can make adversarial training suitable for real-world robot applications. We evaluate a wide variety of robot learning tasks ranging from autonomous driving in a high-fidelity environment\r\namenable to sim-to-real deployment, to mobile robot gesture recognition. Our results demonstrate that, while these techniques make incremental improvements on the trade-off on a relative scale, the negative side-effects caused by\r\nadversarial training still outweigh the improvements by an order of magnitude. We conclude that more substantial advances in robust learning methods are necessary before they can benefit robot learning tasks in practice." acknowledgement: "This work was supported in parts by the ERC-2020-AdG 101020093, National Science Foundation (NSF), and JP\r\nMorgan Graduate Fellowships. We thank Christoph Lampert for inspiring this work.\r\n" article_number: '2204.07373' article_processing_charge: No author: - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Alexander full_name: Amini, Alexander last_name: Amini - first_name: Daniela full_name: Rus, Daniela last_name: Rus - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: Lechner M, Amini A, Rus D, Henzinger TA. Revisiting the adversarial robustness-accuracy tradeoff in robot learning. arXiv. doi:10.48550/arXiv.2204.07373 apa: Lechner, M., Amini, A., Rus, D., & Henzinger, T. A. (n.d.). Revisiting the adversarial robustness-accuracy tradeoff in robot learning. arXiv. https://doi.org/10.48550/arXiv.2204.07373 chicago: Lechner, Mathias, Alexander Amini, Daniela Rus, and Thomas A Henzinger. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2204.07373. ieee: M. Lechner, A. Amini, D. Rus, and T. A. Henzinger, “Revisiting the adversarial robustness-accuracy tradeoff in robot learning,” arXiv. . ista: Lechner M, Amini A, Rus D, Henzinger TA. Revisiting the adversarial robustness-accuracy tradeoff in robot learning. arXiv, 2204.07373. mla: Lechner, Mathias, et al. “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” ArXiv, 2204.07373, doi:10.48550/arXiv.2204.07373. short: M. Lechner, A. Amini, D. Rus, T.A. Henzinger, ArXiv (n.d.). date_created: 2022-05-12T13:20:17Z date_published: 2022-04-15T00:00:00Z date_updated: 2023-08-01T13:36:50Z day: '15' department: - _id: ToHe doi: 10.48550/arXiv.2204.07373 ec_funded: 1 external_id: arxiv: - '2204.07373' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2204.07373 month: '04' oa: 1 oa_version: Preprint project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: arXiv publication_status: submitted related_material: record: - id: '11362' relation: dissertation_contains status: public - id: '12704' relation: later_version status: public status: public title: Revisiting the adversarial robustness-accuracy tradeoff in robot learning type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2022' ... --- _id: '10891' abstract: - lang: eng text: We present a formal framework for the online black-box monitoring of software using monitors with quantitative verdict functions. Quantitative verdict functions have several advantages. First, quantitative monitors can be approximate, i.e., the value of the verdict function does not need to correspond exactly to the value of the property under observation. Second, quantitative monitors can be quantified universally, i.e., for every possible observed behavior, the monitor tries to make the best effort to estimate the value of the property under observation. Third, quantitative monitors can watch boolean as well as quantitative properties, such as average response time. Fourth, quantitative monitors can use non-finite-state resources, such as counters. As a consequence, quantitative monitors can be compared according to how many resources they use (e.g., the number of counters) and how precisely they approximate the property under observation. This allows for a rich spectrum of cost-precision trade-offs in monitoring software. acknowledgement: The formal framework for quantitative monitoring which is presented in this invited talk was defined jointly with N. Ege Saraç at LICS 2021. This work was supported in part by the Wittgenstein Award Z211-N23 of the Austrian Science Fund. article_processing_charge: No author: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: 'Henzinger TA. Quantitative monitoring of software. In: Software Verification. Vol 13124. LNCS. Springer Nature; 2022:3-6. doi:10.1007/978-3-030-95561-8_1' apa: 'Henzinger, T. A. (2022). Quantitative monitoring of software. In Software Verification (Vol. 13124, pp. 3–6). New Haven, CT, United States: Springer Nature. https://doi.org/10.1007/978-3-030-95561-8_1' chicago: Henzinger, Thomas A. “Quantitative Monitoring of Software.” In Software Verification, 13124:3–6. LNCS. Springer Nature, 2022. https://doi.org/10.1007/978-3-030-95561-8_1. ieee: T. A. Henzinger, “Quantitative monitoring of software,” in Software Verification, New Haven, CT, United States, 2022, vol. 13124, pp. 3–6. ista: 'Henzinger TA. 2022. Quantitative monitoring of software. Software Verification. NSV: Numerical Software VerificationLNCS vol. 13124, 3–6.' mla: Henzinger, Thomas A. “Quantitative Monitoring of Software.” Software Verification, vol. 13124, Springer Nature, 2022, pp. 3–6, doi:10.1007/978-3-030-95561-8_1. short: T.A. Henzinger, in:, Software Verification, Springer Nature, 2022, pp. 3–6. conference: end_date: 2021-10-19 location: New Haven, CT, United States name: 'NSV: Numerical Software Verification' start_date: 2021-10-18 date_created: 2022-03-20T23:01:40Z date_published: 2022-02-22T00:00:00Z date_updated: 2023-08-03T06:11:55Z day: '22' department: - _id: ToHe doi: 10.1007/978-3-030-95561-8_1 external_id: isi: - '000771713200001' intvolume: ' 13124' isi: 1 language: - iso: eng month: '02' oa_version: None page: 3-6 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Software Verification publication_identifier: eissn: - 1611-3349 isbn: - '9783030955601' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' series_title: LNCS status: public title: Quantitative monitoring of software type: conference user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 13124 year: '2022' ... --- _id: '11355' abstract: - lang: eng text: "Contract-based design is a promising methodology for taming the complexity of developing sophisticated systems. A formal contract distinguishes between assumptions, which are constraints that the designer of a component puts on the environments in which the component can be used safely, and guarantees, which are promises that the designer asks from the team that implements the component. A theory of formal contracts can be formalized as an interface theory, which supports the composition and refinement of both assumptions and guarantees.\r\nAlthough there is a rich landscape of contract-based design methods that address functional and extra-functional properties, we present the first interface theory that is designed for ensuring system-wide security properties. Our framework provides a refinement relation and a composition operation that support both incremental design and independent implementability. We develop our theory for both stateless and stateful interfaces. We illustrate the applicability of our framework with an example inspired from the automotive domain." acknowledgement: This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 956123 and was funded in part by the FWF project W1255-N23 and by the ERC-2020-AdG 101020093. alternative_title: - LNCS article_processing_charge: No author: - first_name: Ezio full_name: Bartocci, Ezio last_name: Bartocci - first_name: Thomas full_name: Ferrere, Thomas id: 40960E6E-F248-11E8-B48F-1D18A9856A87 last_name: Ferrere orcid: 0000-0001-5199-3143 - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Dejan full_name: Nickovic, Dejan id: 41BCEE5C-F248-11E8-B48F-1D18A9856A87 last_name: Nickovic - first_name: Ana Oliveira full_name: Da Costa, Ana Oliveira last_name: Da Costa citation: ama: 'Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. Information-flow interfaces. In: Fundamental Approaches to Software Engineering. Vol 13241. Springer Nature; 2022:3-22. doi:10.1007/978-3-030-99429-7_1' apa: 'Bartocci, E., Ferrere, T., Henzinger, T. A., Nickovic, D., & Da Costa, A. O. (2022). Information-flow interfaces. In Fundamental Approaches to Software Engineering (Vol. 13241, pp. 3–22). Munich, Germany: Springer Nature. https://doi.org/10.1007/978-3-030-99429-7_1' chicago: Bartocci, Ezio, Thomas Ferrere, Thomas A Henzinger, Dejan Nickovic, and Ana Oliveira Da Costa. “Information-Flow Interfaces.” In Fundamental Approaches to Software Engineering, 13241:3–22. Springer Nature, 2022. https://doi.org/10.1007/978-3-030-99429-7_1. ieee: E. Bartocci, T. Ferrere, T. A. Henzinger, D. Nickovic, and A. O. Da Costa, “Information-flow interfaces,” in Fundamental Approaches to Software Engineering, Munich, Germany, 2022, vol. 13241, pp. 3–22. ista: 'Bartocci E, Ferrere T, Henzinger TA, Nickovic D, Da Costa AO. 2022. Information-flow interfaces. Fundamental Approaches to Software Engineering. FASE: Fundamental Approaches to Software Engineering, LNCS, vol. 13241, 3–22.' mla: Bartocci, Ezio, et al. “Information-Flow Interfaces.” Fundamental Approaches to Software Engineering, vol. 13241, Springer Nature, 2022, pp. 3–22, doi:10.1007/978-3-030-99429-7_1. short: E. Bartocci, T. Ferrere, T.A. Henzinger, D. Nickovic, A.O. Da Costa, in:, Fundamental Approaches to Software Engineering, Springer Nature, 2022, pp. 3–22. conference: end_date: 2022-04-07 location: Munich, Germany name: 'FASE: Fundamental Approaches to Software Engineering' start_date: 2022-04-02 date_created: 2022-05-08T22:01:44Z date_published: 2022-03-29T00:00:00Z date_updated: 2023-08-03T07:03:40Z day: '29' ddc: - '000' department: - _id: ToHe doi: 10.1007/978-3-030-99429-7_1 ec_funded: 1 external_id: isi: - '000782393600001' file: - access_level: open_access checksum: 7f6f860b20b8de2a249e9c1b4eee15cf content_type: application/pdf creator: dernst date_created: 2022-05-09T06:52:44Z date_updated: 2022-05-09T06:52:44Z file_id: '11357' file_name: 2022_LNCS_Bartocci.pdf file_size: 479146 relation: main_file success: 1 file_date_updated: 2022-05-09T06:52:44Z has_accepted_license: '1' intvolume: ' 13241' isi: 1 language: - iso: eng month: '03' oa: 1 oa_version: Published Version page: 3-22 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: Fundamental Approaches to Software Engineering publication_identifier: eissn: - 1611-3349 isbn: - '9783030994280' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Information-flow interfaces tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 13241 year: '2022' ... --- _id: '11775' abstract: - lang: eng text: 'Quantitative monitoring can be universal and approximate: For every finite sequence of observations, the specification provides a value and the monitor outputs a best-effort approximation of it. The quality of the approximation may depend on the resources that are available to the monitor. By taking to the limit the sequences of specification values and monitor outputs, we obtain precision-resource trade-offs also for limit monitoring. This paper provides a formal framework for studying such trade-offs using an abstract interpretation for monitors: For each natural number n, the aggregate semantics of a monitor at time n is an equivalence relation over all sequences of at most n observations so that two equivalent sequences are indistinguishable to the monitor and thus mapped to the same output. This abstract interpretation of quantitative monitors allows us to measure the number of equivalence classes (or “resource use”) that is necessary for a certain precision up to a certain time, or at any time. Our framework offers several insights. For example, we identify a family of specifications for which any resource-optimal exact limit monitor is independent of any error permitted over finite traces. Moreover, we present a specification for which any resource-optimal approximate limit monitor does not minimize its resource use at any time. ' acknowledgement: We thank the anonymous reviewers for their helpful comments. This work was supported in part by the ERC-2020-AdG 101020093. alternative_title: - LNCS article_processing_charge: Yes author: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Nicolas Adrien full_name: Mazzocchi, Nicolas Adrien id: b26baa86-3308-11ec-87b0-8990f34baa85 last_name: Mazzocchi - first_name: Naci E full_name: Sarac, Naci E id: 8C6B42F8-C8E6-11E9-A03A-F2DCE5697425 last_name: Sarac citation: ama: 'Henzinger TA, Mazzocchi NA, Sarac NE. Abstract monitors for quantitative specifications. In: 22nd International Conference on Runtime Verification. Vol 13498. Springer Nature; 2022:200-220. doi:10.1007/978-3-031-17196-3_11' apa: 'Henzinger, T. A., Mazzocchi, N. A., & Sarac, N. E. (2022). Abstract monitors for quantitative specifications. In 22nd International Conference on Runtime Verification (Vol. 13498, pp. 200–220). Tbilisi, Georgia: Springer Nature. https://doi.org/10.1007/978-3-031-17196-3_11' chicago: Henzinger, Thomas A, Nicolas Adrien Mazzocchi, and Naci E Sarac. “Abstract Monitors for Quantitative Specifications.” In 22nd International Conference on Runtime Verification, 13498:200–220. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-17196-3_11. ieee: T. A. Henzinger, N. A. Mazzocchi, and N. E. Sarac, “Abstract monitors for quantitative specifications,” in 22nd International Conference on Runtime Verification, Tbilisi, Georgia, 2022, vol. 13498, pp. 200–220. ista: 'Henzinger TA, Mazzocchi NA, Sarac NE. 2022. Abstract monitors for quantitative specifications. 22nd International Conference on Runtime Verification. RV: Runtime Verification, LNCS, vol. 13498, 200–220.' mla: Henzinger, Thomas A., et al. “Abstract Monitors for Quantitative Specifications.” 22nd International Conference on Runtime Verification, vol. 13498, Springer Nature, 2022, pp. 200–20, doi:10.1007/978-3-031-17196-3_11. short: T.A. Henzinger, N.A. Mazzocchi, N.E. Sarac, in:, 22nd International Conference on Runtime Verification, Springer Nature, 2022, pp. 200–220. conference: end_date: 2022-09-30 location: Tbilisi, Georgia name: 'RV: Runtime Verification' start_date: 2022-09-28 date_created: 2022-08-08T17:09:09Z date_published: 2022-09-23T00:00:00Z date_updated: 2023-08-03T13:38:46Z day: '23' ddc: - '000' department: - _id: GradSch - _id: ToHe doi: 10.1007/978-3-031-17196-3_11 ec_funded: 1 external_id: isi: - '000866539700011' file: - access_level: open_access checksum: 05c7dcfbb9053a98f46441fb2eccb213 content_type: application/pdf creator: dernst date_created: 2023-01-20T07:34:50Z date_updated: 2023-01-20T07:34:50Z file_id: '12317' file_name: 2022_LNCS_RV_Henzinger.pdf file_size: 477110 relation: main_file success: 1 file_date_updated: 2023-01-20T07:34:50Z has_accepted_license: '1' intvolume: ' 13498' isi: 1 language: - iso: eng month: '09' oa: 1 oa_version: Published Version page: 200-220 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 22nd International Conference on Runtime Verification publication_identifier: issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: Abstract monitors for quantitative specifications tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 13498 year: '2022' ... --- _id: '12147' abstract: - lang: eng text: Continuous-time neural networks are a class of machine learning systems that can tackle representation learning on spatiotemporal decision-making tasks. These models are typically represented by continuous differential equations. However, their expressive power when they are deployed on computers is bottlenecked by numerical differential equation solvers. This limitation has notably slowed down the scaling and understanding of numerous natural physical phenomena such as the dynamics of nervous systems. Ideally, we would circumvent this bottleneck by solving the given dynamical system in closed form. This is known to be intractable in general. Here, we show that it is possible to closely approximate the interaction between neurons and synapses—the building blocks of natural and artificial neural networks—constructed by liquid time-constant networks efficiently in closed form. To this end, we compute a tightly bounded approximation of the solution of an integral appearing in liquid time-constant dynamics that has had no known closed-form solution so far. This closed-form solution impacts the design of continuous-time and continuous-depth neural models. For instance, since time appears explicitly in closed form, the formulation relaxes the need for complex numerical solvers. Consequently, we obtain models that are between one and five orders of magnitude faster in training and inference compared with differential equation-based counterparts. More importantly, in contrast to ordinary differential equation-based continuous networks, closed-form networks can scale remarkably well compared with other deep learning instances. Lastly, as these models are derived from liquid networks, they show good performance in time-series modelling compared with advanced recurrent neural network models. acknowledgement: This research was supported in part by the AI2050 program at Schmidt Futures (grant G-22-63172), the Boeing Company, and the United States Air Force Research Laboratory and the United States Air Force Artificial Intelligence Accelerator and was accomplished under cooperative agreement number FA8750-19-2-1000. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the United States Air Force or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes, notwithstanding any copyright notation herein. This work was further supported by The Boeing Company and Office of Naval Research grant N00014-18-1-2830. M.T. is supported by the Poul Due Jensen Foundation, grant 883901. M.L. was supported in part by the Austrian Science Fund under grant Z211-N23 (Wittgenstein Award). A.A. was supported by the National Science Foundation Graduate Research Fellowship Program. We thank T.-H. Wang, P. Kao, M. Chahine, W. Xiao, X. Li, L. Yin and Y. Ben for useful suggestions and for testing of CfC models to confirm the results across other domains. article_processing_charge: No article_type: original author: - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Alexander full_name: Amini, Alexander last_name: Amini - first_name: Lucas full_name: Liebenwein, Lucas last_name: Liebenwein - first_name: Aaron full_name: Ray, Aaron last_name: Ray - first_name: Max full_name: Tschaikowski, Max last_name: Tschaikowski - first_name: Gerald full_name: Teschl, Gerald last_name: Teschl - first_name: Daniela full_name: Rus, Daniela last_name: Rus citation: ama: Hasani R, Lechner M, Amini A, et al. Closed-form continuous-time neural networks. Nature Machine Intelligence. 2022;4(11):992-1003. doi:10.1038/s42256-022-00556-7 apa: Hasani, R., Lechner, M., Amini, A., Liebenwein, L., Ray, A., Tschaikowski, M., … Rus, D. (2022). Closed-form continuous-time neural networks. Nature Machine Intelligence. Springer Nature. https://doi.org/10.1038/s42256-022-00556-7 chicago: Hasani, Ramin, Mathias Lechner, Alexander Amini, Lucas Liebenwein, Aaron Ray, Max Tschaikowski, Gerald Teschl, and Daniela Rus. “Closed-Form Continuous-Time Neural Networks.” Nature Machine Intelligence. Springer Nature, 2022. https://doi.org/10.1038/s42256-022-00556-7. ieee: R. Hasani et al., “Closed-form continuous-time neural networks,” Nature Machine Intelligence, vol. 4, no. 11. Springer Nature, pp. 992–1003, 2022. ista: Hasani R, Lechner M, Amini A, Liebenwein L, Ray A, Tschaikowski M, Teschl G, Rus D. 2022. Closed-form continuous-time neural networks. Nature Machine Intelligence. 4(11), 992–1003. mla: Hasani, Ramin, et al. “Closed-Form Continuous-Time Neural Networks.” Nature Machine Intelligence, vol. 4, no. 11, Springer Nature, 2022, pp. 992–1003, doi:10.1038/s42256-022-00556-7. short: R. Hasani, M. Lechner, A. Amini, L. Liebenwein, A. Ray, M. Tschaikowski, G. Teschl, D. Rus, Nature Machine Intelligence 4 (2022) 992–1003. date_created: 2023-01-12T12:07:21Z date_published: 2022-11-15T00:00:00Z date_updated: 2023-08-04T09:00:10Z day: '15' ddc: - '000' department: - _id: ToHe doi: 10.1038/s42256-022-00556-7 external_id: arxiv: - '2106.13898' isi: - '000884215600003' file: - access_level: open_access checksum: b4789122ce04bfb4ac042390f59aaa8b content_type: application/pdf creator: dernst date_created: 2023-01-24T09:49:44Z date_updated: 2023-01-24T09:49:44Z file_id: '12355' file_name: 2022_NatureMachineIntelligence_Hasani.pdf file_size: 3259553 relation: main_file success: 1 file_date_updated: 2023-01-24T09:49:44Z has_accepted_license: '1' intvolume: ' 4' isi: 1 issue: '11' keyword: - Artificial Intelligence - Computer Networks and Communications - Computer Vision and Pattern Recognition - Human-Computer Interaction - Software language: - iso: eng month: '11' oa: 1 oa_version: Published Version page: 992-1003 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Nature Machine Intelligence publication_identifier: issn: - 2522-5839 publication_status: published publisher: Springer Nature quality_controlled: '1' related_material: link: - relation: erratum url: https://doi.org/10.1038/s42256-022-00597-y scopus_import: '1' status: public title: Closed-form continuous-time neural networks tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 4 year: '2022' ... --- _id: '11362' abstract: - lang: eng text: "Deep learning has enabled breakthroughs in challenging computing problems and has emerged as the standard problem-solving tool for computer vision and natural language processing tasks.\r\nOne exception to this trend is safety-critical tasks where robustness and resilience requirements contradict the black-box nature of neural networks. \r\nTo deploy deep learning methods for these tasks, it is vital to provide guarantees on neural network agents' safety and robustness criteria. \r\nThis can be achieved by developing formal verification methods to verify the safety and robustness properties of neural networks.\r\n\r\nOur goal is to design, develop and assess safety verification methods for neural networks to improve their reliability and trustworthiness in real-world applications.\r\nThis thesis establishes techniques for the verification of compressed and adversarially trained models as well as the design of novel neural networks for verifiably safe decision-making.\r\n\r\nFirst, we establish the problem of verifying quantized neural networks. Quantization is a technique that trades numerical precision for the computational efficiency of running a neural network and is widely adopted in industry.\r\nWe show that neglecting the reduced precision when verifying a neural network can lead to wrong conclusions about the robustness and safety of the network, highlighting that novel techniques for quantized network verification are necessary. We introduce several bit-exact verification methods explicitly designed for quantized neural networks and experimentally confirm on realistic networks that the network's robustness and other formal properties are affected by the quantization.\r\n\r\nFurthermore, we perform a case study providing evidence that adversarial training, a standard technique for making neural networks more robust, has detrimental effects on the network's performance. This robustness-accuracy tradeoff has been studied before regarding the accuracy obtained on classification datasets where each data point is independent of all other data points. On the other hand, we investigate the tradeoff empirically in robot learning settings where a both, a high accuracy and a high robustness, are desirable.\r\nOur results suggest that the negative side-effects of adversarial training outweigh its robustness benefits in practice.\r\n\r\nFinally, we consider the problem of verifying safety when running a Bayesian neural network policy in a feedback loop with systems over the infinite time horizon. Bayesian neural networks are probabilistic models for learning uncertainties in the data and are therefore often used on robotic and healthcare applications where data is inherently stochastic.\r\nWe introduce a method for recalibrating Bayesian neural networks so that they yield probability distributions over safe decisions only.\r\nOur method learns a safety certificate that guarantees safety over the infinite time horizon to determine which decisions are safe in every possible state of the system.\r\nWe demonstrate the effectiveness of our approach on a series of reinforcement learning benchmarks." alternative_title: - ISTA Thesis article_processing_charge: No author: - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner citation: ama: Lechner M. Learning verifiable representations. 2022. doi:10.15479/at:ista:11362 apa: Lechner, M. (2022). Learning verifiable representations. Institute of Science and Technology Austria. https://doi.org/10.15479/at:ista:11362 chicago: Lechner, Mathias. “Learning Verifiable Representations.” Institute of Science and Technology Austria, 2022. https://doi.org/10.15479/at:ista:11362. ieee: M. Lechner, “Learning verifiable representations,” Institute of Science and Technology Austria, 2022. ista: Lechner M. 2022. Learning verifiable representations. Institute of Science and Technology Austria. mla: Lechner, Mathias. Learning Verifiable Representations. Institute of Science and Technology Austria, 2022, doi:10.15479/at:ista:11362. short: M. Lechner, Learning Verifiable Representations, Institute of Science and Technology Austria, 2022. date_created: 2022-05-12T07:14:01Z date_published: 2022-05-12T00:00:00Z date_updated: 2023-08-17T06:58:38Z day: '12' ddc: - '004' degree_awarded: PhD department: - _id: GradSch - _id: ToHe doi: 10.15479/at:ista:11362 ec_funded: 1 file: - access_level: closed checksum: 8eefa9c7c10ca7e1a2ccdd731962a645 content_type: application/zip creator: mlechner date_created: 2022-05-13T12:33:26Z date_updated: 2022-05-13T12:49:00Z file_id: '11378' file_name: src.zip file_size: 13210143 relation: source_file - access_level: open_access checksum: 1b9e1e5a9a83ed9d89dad2f5133dc026 content_type: application/pdf creator: mlechner date_created: 2022-05-16T08:02:28Z date_updated: 2022-05-17T15:19:39Z file_id: '11382' file_name: thesis_main-a2.pdf file_size: 2732536 relation: main_file file_date_updated: 2022-05-17T15:19:39Z has_accepted_license: '1' keyword: - neural networks - verification - machine learning language: - iso: eng license: https://creativecommons.org/licenses/by-nd/4.0/ month: '05' oa: 1 oa_version: Published Version page: '124' project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication_identifier: isbn: - 978-3-99078-017-6 publication_status: published publisher: Institute of Science and Technology Austria related_material: record: - id: '10665' relation: part_of_dissertation status: public - id: '10667' relation: part_of_dissertation status: public - id: '11366' relation: part_of_dissertation status: public - id: '7808' relation: part_of_dissertation status: public - id: '10666' relation: part_of_dissertation status: public status: public supervisor: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 title: Learning verifiable representations tmp: image: /image/cc_by_nd.png legal_code_url: https://creativecommons.org/licenses/by-nd/4.0/legalcode name: Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0) short: CC BY-ND (4.0) type: dissertation user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2022' ... --- _id: '12302' abstract: - lang: eng text: 'We propose a novel algorithm to decide the language inclusion between (nondeterministic) Büchi automata, a PSPACE-complete problem. Our approach, like others before, leverage a notion of quasiorder to prune the search for a counterexample by discarding candidates which are subsumed by others for the quasiorder. Discarded candidates are guaranteed to not compromise the completeness of the algorithm. The novelty of our work lies in the quasiorder used to discard candidates. We introduce FORQs (family of right quasiorders) that we obtain by adapting the notion of family of right congruences put forward by Maler and Staiger in 1993. We define a FORQ-based inclusion algorithm which we prove correct and instantiate it for a specific FORQ, called the structural FORQ, induced by the Büchi automaton to the right of the inclusion sign. The resulting implementation, called FORKLIFT, scales up better than the state-of-the-art on a variety of benchmarks including benchmarks from program verification and theorem proving for word combinatorics. Artifact: https://doi.org/10.5281/zenodo.6552870' acknowledgement: This work was partially funded by the ESF Investing in your future, the Madrid regional project S2018/TCS-4339 BLOQUES, the Spanish project PGC2018-102210-B-I00 BOSCO, the Ramón y Cajal fellowship RYC-2016-20281, and the ERC grant PR1001ERC02. alternative_title: - LNCS article_processing_charge: No author: - first_name: Kyveli full_name: Doveri, Kyveli last_name: Doveri - first_name: Pierre full_name: Ganty, Pierre last_name: Ganty - first_name: Nicolas Adrien full_name: Mazzocchi, Nicolas Adrien id: b26baa86-3308-11ec-87b0-8990f34baa85 last_name: Mazzocchi citation: ama: 'Doveri K, Ganty P, Mazzocchi NA. FORQ-based language inclusion formal testing. In: Computer Aided Verification. Vol 13372. Springer Nature; 2022:109-129. doi:10.1007/978-3-031-13188-2_6' apa: 'Doveri, K., Ganty, P., & Mazzocchi, N. A. (2022). FORQ-based language inclusion formal testing. In Computer Aided Verification (Vol. 13372, pp. 109–129). Haifa, Israel: Springer Nature. https://doi.org/10.1007/978-3-031-13188-2_6' chicago: Doveri, Kyveli, Pierre Ganty, and Nicolas Adrien Mazzocchi. “FORQ-Based Language Inclusion Formal Testing.” In Computer Aided Verification, 13372:109–29. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-13188-2_6. ieee: K. Doveri, P. Ganty, and N. A. Mazzocchi, “FORQ-based language inclusion formal testing,” in Computer Aided Verification, Haifa, Israel, 2022, vol. 13372, pp. 109–129. ista: 'Doveri K, Ganty P, Mazzocchi NA. 2022. FORQ-based language inclusion formal testing. Computer Aided Verification. CAV: Computer Aided Verification, LNCS, vol. 13372, 109–129.' mla: Doveri, Kyveli, et al. “FORQ-Based Language Inclusion Formal Testing.” Computer Aided Verification, vol. 13372, Springer Nature, 2022, pp. 109–29, doi:10.1007/978-3-031-13188-2_6. short: K. Doveri, P. Ganty, N.A. Mazzocchi, in:, Computer Aided Verification, Springer Nature, 2022, pp. 109–129. conference: end_date: 2022-08-10 location: Haifa, Israel name: 'CAV: Computer Aided Verification' start_date: 2022-08-07 date_created: 2023-01-16T10:06:31Z date_published: 2022-08-06T00:00:00Z date_updated: 2023-09-05T15:13:36Z day: '06' ddc: - '000' department: - _id: ToHe doi: 10.1007/978-3-031-13188-2_6 ec_funded: 1 external_id: arxiv: - '2207.13549' isi: - '000870310500006' file: - access_level: open_access checksum: edc363b1be5447a09063e115c247918a content_type: application/pdf creator: dernst date_created: 2023-01-30T12:51:02Z date_updated: 2023-01-30T12:51:02Z file_id: '12465' file_name: 2022_LNCS_Doveri.pdf file_size: 497682 relation: main_file success: 1 file_date_updated: 2023-01-30T12:51:02Z has_accepted_license: '1' intvolume: ' 13372' isi: 1 language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: 109-129 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: Computer Aided Verification publication_identifier: eisbn: - '9783031131882' eissn: - 1611-3349 isbn: - '9783031131875' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: FORQ-based language inclusion formal testing tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 13372 year: '2022' ... --- _id: '12175' abstract: - lang: eng text: An automaton is history-deterministic (HD) if one can safely resolve its non-deterministic choices on the fly. In a recent paper, Henzinger, Lehtinen and Totzke studied this in the context of Timed Automata [9], where it was conjectured that the class of timed ω-languages recognised by HD-timed automata strictly extends that of deterministic ones. We provide a proof for this fact. acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, the EPSRC project EP/V025848/1, and the EPSRC project EP/X017796/1. alternative_title: - LNCS article_processing_charge: No author: - first_name: Sougata full_name: Bose, Sougata last_name: Bose - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Karoliina full_name: Lehtinen, Karoliina last_name: Lehtinen - first_name: Sven full_name: Schewe, Sven last_name: Schewe - first_name: Patrick full_name: Totzke, Patrick last_name: Totzke citation: ama: 'Bose S, Henzinger TA, Lehtinen K, Schewe S, Totzke P. History-deterministic timed automata are not determinizable. In: 16th International Conference on Reachability Problems. Vol 13608. Springer Nature; 2022:67-76. doi:10.1007/978-3-031-19135-0_5' apa: 'Bose, S., Henzinger, T. A., Lehtinen, K., Schewe, S., & Totzke, P. (2022). History-deterministic timed automata are not determinizable. In 16th International Conference on Reachability Problems (Vol. 13608, pp. 67–76). Kaiserslautern, Germany: Springer Nature. https://doi.org/10.1007/978-3-031-19135-0_5' chicago: Bose, Sougata, Thomas A Henzinger, Karoliina Lehtinen, Sven Schewe, and Patrick Totzke. “History-Deterministic Timed Automata Are Not Determinizable.” In 16th International Conference on Reachability Problems, 13608:67–76. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-19135-0_5. ieee: S. Bose, T. A. Henzinger, K. Lehtinen, S. Schewe, and P. Totzke, “History-deterministic timed automata are not determinizable,” in 16th International Conference on Reachability Problems, Kaiserslautern, Germany, 2022, vol. 13608, pp. 67–76. ista: 'Bose S, Henzinger TA, Lehtinen K, Schewe S, Totzke P. 2022. History-deterministic timed automata are not determinizable. 16th International Conference on Reachability Problems. RC: Reachability Problems, LNCS, vol. 13608, 67–76.' mla: Bose, Sougata, et al. “History-Deterministic Timed Automata Are Not Determinizable.” 16th International Conference on Reachability Problems, vol. 13608, Springer Nature, 2022, pp. 67–76, doi:10.1007/978-3-031-19135-0_5. short: S. Bose, T.A. Henzinger, K. Lehtinen, S. Schewe, P. Totzke, in:, 16th International Conference on Reachability Problems, Springer Nature, 2022, pp. 67–76. conference: end_date: 2022-10-21 location: Kaiserslautern, Germany name: 'RC: Reachability Problems' start_date: 2022-10-17 date_created: 2023-01-12T12:11:57Z date_published: 2022-10-12T00:00:00Z date_updated: 2023-09-05T15:12:08Z day: '12' department: - _id: ToHe doi: 10.1007/978-3-031-19135-0_5 ec_funded: 1 intvolume: ' 13608' language: - iso: eng main_file_link: - open_access: '1' url: https://hal.science/hal-03849398/ month: '10' oa: 1 oa_version: Preprint page: 67-76 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: 16th International Conference on Reachability Problems publication_identifier: eisbn: - '9783031191350' eissn: - 1611-3349 isbn: - '9783031191343' issn: - 0302-9743 publication_status: published publisher: Springer Nature quality_controlled: '1' scopus_import: '1' status: public title: History-deterministic timed automata are not determinizable type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 13608 year: '2022' ... --- _id: '12510' abstract: - lang: eng text: "We introduce a new statistical verification algorithm that formally quantifies the behavioral robustness of any time-continuous process formulated as a continuous-depth model. Our algorithm solves a set of global optimization (Go) problems over a given time horizon to construct a tight enclosure (Tube) of the set of all process executions starting from a ball of initial states. We call our algorithm GoTube. Through its construction, GoTube ensures that the bounding tube is conservative up to a desired probability and up to a desired tightness.\r\n GoTube is implemented in JAX and optimized to scale to complex continuous-depth neural network models. Compared to advanced reachability analysis tools for time-continuous neural networks, GoTube does not accumulate overapproximation errors between time steps and avoids the infamous wrapping effect inherent in symbolic techniques. We show that GoTube substantially outperforms state-of-the-art verification tools in terms of the size of the initial ball, speed, time-horizon, task completion, and scalability on a large set of experiments.\r\n GoTube is stable and sets the state-of-the-art in terms of its ability to scale to time horizons well beyond what has been previously possible." acknowledgement: SG is funded by the Austrian Science Fund (FWF) project number W1255-N23. ML and TH are supported in part by FWF under grant Z211-N23 (Wittgenstein Award) and the ERC-2020-AdG 101020093. SS is supported by NSF awards DCL-2040599, CCF-1918225, and CPS-1446832. RH and DR are partially supported by Boeing. RG is partially supported by Horizon-2020 ECSEL Project grant No. 783163 (iDev40). article_processing_charge: No article_type: original author: - first_name: Sophie A. full_name: Gruenbacher, Sophie A. last_name: Gruenbacher - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Daniela full_name: Rus, Daniela last_name: Rus - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Scott A. full_name: Smolka, Scott A. last_name: Smolka - first_name: Radu full_name: Grosu, Radu last_name: Grosu citation: ama: 'Gruenbacher SA, Lechner M, Hasani R, et al. GoTube: Scalable statistical verification of continuous-depth models. Proceedings of the AAAI Conference on Artificial Intelligence. 2022;36(6):6755-6764. doi:10.1609/aaai.v36i6.20631' apa: 'Gruenbacher, S. A., Lechner, M., Hasani, R., Rus, D., Henzinger, T. A., Smolka, S. A., & Grosu, R. (2022). GoTube: Scalable statistical verification of continuous-depth models. Proceedings of the AAAI Conference on Artificial Intelligence. Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v36i6.20631' chicago: 'Gruenbacher, Sophie A., Mathias Lechner, Ramin Hasani, Daniela Rus, Thomas A Henzinger, Scott A. Smolka, and Radu Grosu. “GoTube: Scalable Statistical Verification of Continuous-Depth Models.” Proceedings of the AAAI Conference on Artificial Intelligence. Association for the Advancement of Artificial Intelligence, 2022. https://doi.org/10.1609/aaai.v36i6.20631.' ieee: 'S. A. Gruenbacher et al., “GoTube: Scalable statistical verification of continuous-depth models,” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 6. Association for the Advancement of Artificial Intelligence, pp. 6755–6764, 2022.' ista: 'Gruenbacher SA, Lechner M, Hasani R, Rus D, Henzinger TA, Smolka SA, Grosu R. 2022. GoTube: Scalable statistical verification of continuous-depth models. Proceedings of the AAAI Conference on Artificial Intelligence. 36(6), 6755–6764.' mla: 'Gruenbacher, Sophie A., et al. “GoTube: Scalable Statistical Verification of Continuous-Depth Models.” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 6, Association for the Advancement of Artificial Intelligence, 2022, pp. 6755–64, doi:10.1609/aaai.v36i6.20631.' short: S.A. Gruenbacher, M. Lechner, R. Hasani, D. Rus, T.A. Henzinger, S.A. Smolka, R. Grosu, Proceedings of the AAAI Conference on Artificial Intelligence 36 (2022) 6755–6764. date_created: 2023-02-05T17:27:42Z date_published: 2022-06-28T00:00:00Z date_updated: 2023-09-26T10:46:59Z day: '28' department: - _id: ToHe doi: 10.1609/aaai.v36i6.20631 ec_funded: 1 external_id: arxiv: - '2107.08467' intvolume: ' 36' issue: '6' keyword: - General Medicine language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2107.08467 month: '06' oa: 1 oa_version: Preprint page: 6755-6764 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software publication: Proceedings of the AAAI Conference on Artificial Intelligence publication_identifier: eissn: - 2374-3468 isbn: - '978577358350' issn: - 2159-5399 publication_status: published publisher: Association for the Advancement of Artificial Intelligence quality_controlled: '1' scopus_import: '1' status: public title: 'GoTube: Scalable statistical verification of continuous-depth models' type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 36 year: '2022' ... --- _id: '12511' abstract: - lang: eng text: "We consider the problem of formally verifying almost-sure (a.s.) asymptotic stability in discrete-time nonlinear stochastic control systems. While verifying stability in deterministic control systems is extensively studied in the literature, verifying stability in stochastic control systems is an open problem. The few existing works on this topic either consider only specialized forms of stochasticity or make restrictive assumptions on the system, rendering them inapplicable to learning algorithms with neural network policies. \r\n In this work, we present an approach for general nonlinear stochastic control problems with two novel aspects: (a) instead of classical stochastic extensions of Lyapunov functions, we use ranking supermartingales (RSMs) to certify a.s. asymptotic stability, and (b) we present a method for learning neural network RSMs. \r\n We prove that our approach guarantees a.s. asymptotic stability of the system and\r\n provides the first method to obtain bounds on the stabilization time, which stochastic Lyapunov functions do not.\r\n Finally, we validate our approach experimentally on a set of nonlinear stochastic reinforcement learning environments with neural network policies." acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093, ERC CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation programme\r\nunder the Marie Skłodowska-Curie Grant Agreement No. 665385." article_processing_charge: No article_type: original author: - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: Lechner M, Zikelic D, Chatterjee K, Henzinger TA. Stability verification in stochastic control systems via neural network supermartingales. Proceedings of the AAAI Conference on Artificial Intelligence. 2022;36(7):7326-7336. doi:10.1609/aaai.v36i7.20695 apa: Lechner, M., Zikelic, D., Chatterjee, K., & Henzinger, T. A. (2022). Stability verification in stochastic control systems via neural network supermartingales. Proceedings of the AAAI Conference on Artificial Intelligence. Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v36i7.20695 chicago: Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, and Thomas A Henzinger. “Stability Verification in Stochastic Control Systems via Neural Network Supermartingales.” Proceedings of the AAAI Conference on Artificial Intelligence. Association for the Advancement of Artificial Intelligence, 2022. https://doi.org/10.1609/aaai.v36i7.20695. ieee: M. Lechner, D. Zikelic, K. Chatterjee, and T. A. Henzinger, “Stability verification in stochastic control systems via neural network supermartingales,” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 7. Association for the Advancement of Artificial Intelligence, pp. 7326–7336, 2022. ista: Lechner M, Zikelic D, Chatterjee K, Henzinger TA. 2022. Stability verification in stochastic control systems via neural network supermartingales. Proceedings of the AAAI Conference on Artificial Intelligence. 36(7), 7326–7336. mla: Lechner, Mathias, et al. “Stability Verification in Stochastic Control Systems via Neural Network Supermartingales.” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 36, no. 7, Association for the Advancement of Artificial Intelligence, 2022, pp. 7326–36, doi:10.1609/aaai.v36i7.20695. short: M. Lechner, D. Zikelic, K. Chatterjee, T.A. Henzinger, Proceedings of the AAAI Conference on Artificial Intelligence 36 (2022) 7326–7336. date_created: 2023-02-05T17:29:50Z date_published: 2022-06-28T00:00:00Z date_updated: 2023-11-30T10:55:37Z day: '28' department: - _id: ToHe - _id: KrCh doi: 10.1609/aaai.v36i7.20695 ec_funded: 1 external_id: arxiv: - '2112.09495' intvolume: ' 36' issue: '7' keyword: - General Medicine language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2112.09495 month: '06' oa: 1 oa_version: Preprint page: 7326-7336 project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: Proceedings of the AAAI Conference on Artificial Intelligence publication_identifier: eissn: - 2374-3468 isbn: - '9781577358350' issn: - 2159-5399 publication_status: published publisher: Association for the Advancement of Artificial Intelligence quality_controlled: '1' related_material: record: - id: '14539' relation: dissertation_contains status: public scopus_import: '1' status: public title: Stability verification in stochastic control systems via neural network supermartingales type: journal_article user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 36 year: '2022' ... --- _id: '14601' abstract: - lang: eng text: "In this work, we address the problem of learning provably stable neural\r\nnetwork policies for stochastic control systems. While recent work has\r\ndemonstrated the feasibility of certifying given policies using martingale\r\ntheory, the problem of how to learn such policies is little explored. Here, we\r\nstudy the effectiveness of jointly learning a policy together with a martingale\r\ncertificate that proves its stability using a single learning algorithm. We\r\nobserve that the joint optimization problem becomes easily stuck in local\r\nminima when starting from a randomly initialized policy. Our results suggest\r\nthat some form of pre-training of the policy is required for the joint\r\noptimization to repair and verify the policy successfully." article_processing_charge: No author: - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 citation: ama: Zikelic D, Lechner M, Chatterjee K, Henzinger TA. Learning stabilizing policies in stochastic control systems. arXiv. doi:10.48550/arXiv.2205.11991 apa: Zikelic, D., Lechner, M., Chatterjee, K., & Henzinger, T. A. (n.d.). Learning stabilizing policies in stochastic control systems. arXiv. https://doi.org/10.48550/arXiv.2205.11991 chicago: Zikelic, Dorde, Mathias Lechner, Krishnendu Chatterjee, and Thomas A Henzinger. “Learning Stabilizing Policies in Stochastic Control Systems.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2205.11991. ieee: D. Zikelic, M. Lechner, K. Chatterjee, and T. A. Henzinger, “Learning stabilizing policies in stochastic control systems,” arXiv. . ista: Zikelic D, Lechner M, Chatterjee K, Henzinger TA. Learning stabilizing policies in stochastic control systems. arXiv, 10.48550/arXiv.2205.11991. mla: Zikelic, Dorde, et al. “Learning Stabilizing Policies in Stochastic Control Systems.” ArXiv, doi:10.48550/arXiv.2205.11991. short: D. Zikelic, M. Lechner, K. Chatterjee, T.A. Henzinger, ArXiv (n.d.). date_created: 2023-11-24T13:22:30Z date_published: 2022-05-24T00:00:00Z date_updated: 2023-11-30T10:55:37Z day: '24' department: - _id: KrCh - _id: ToHe doi: 10.48550/arXiv.2205.11991 ec_funded: 1 external_id: arxiv: - '2205.11991' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2205.11991 month: '05' oa: 1 oa_version: Preprint project: - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: arXiv publication_status: submitted related_material: record: - id: '14539' relation: dissertation_contains status: public status: public title: Learning stabilizing policies in stochastic control systems type: preprint user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2022' ... --- _id: '14600' abstract: - lang: eng text: We study the problem of learning controllers for discrete-time non-linear stochastic dynamical systems with formal reach-avoid guarantees. This work presents the first method for providing formal reach-avoid guarantees, which combine and generalize stability and safety guarantees, with a tolerable probability threshold $p\in[0,1]$ over the infinite time horizon. Our method leverages advances in machine learning literature and it represents formal certificates as neural networks. In particular, we learn a certificate in the form of a reach-avoid supermartingale (RASM), a novel notion that we introduce in this work. Our RASMs provide reachability and avoidance guarantees by imposing constraints on what can be viewed as a stochastic extension of level sets of Lyapunov functions for deterministic systems. Our approach solves several important problems -- it can be used to learn a control policy from scratch, to verify a reach-avoid specification for a fixed control policy, or to fine-tune a pre-trained policy if it does not satisfy the reach-avoid specification. We validate our approach on $3$ stochastic non-linear reinforcement learning tasks. article_processing_charge: No author: - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X citation: ama: Zikelic D, Lechner M, Henzinger TA, Chatterjee K. Learning control policies for stochastic systems with reach-avoid guarantees. arXiv. doi:10.48550/ARXIV.2210.05308 apa: Zikelic, D., Lechner, M., Henzinger, T. A., & Chatterjee, K. (n.d.). Learning control policies for stochastic systems with reach-avoid guarantees. arXiv. https://doi.org/10.48550/ARXIV.2210.05308 chicago: Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2210.05308. ieee: D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control policies for stochastic systems with reach-avoid guarantees,” arXiv. . ista: Zikelic D, Lechner M, Henzinger TA, Chatterjee K. Learning control policies for stochastic systems with reach-avoid guarantees. arXiv, 10.48550/ARXIV.2210.05308. mla: Zikelic, Dorde, et al. “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.” ArXiv, doi:10.48550/ARXIV.2210.05308. short: D. Zikelic, M. Lechner, T.A. Henzinger, K. Chatterjee, ArXiv (n.d.). date_created: 2023-11-24T13:10:09Z date_published: 2022-11-29T00:00:00Z date_updated: 2024-01-22T14:08:29Z day: '29' department: - _id: KrCh - _id: ToHe doi: 10.48550/ARXIV.2210.05308 ec_funded: 1 external_id: arxiv: - '2210.05308' language: - iso: eng license: https://creativecommons.org/licenses/by-sa/4.0/ main_file_link: - open_access: '1' url: https://arxiv.org/abs/2210.05308 month: '11' oa: 1 oa_version: Preprint project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 62781420-2b32-11ec-9570-8d9b63373d4d call_identifier: H2020 grant_number: '101020093' name: Vigilant Algorithmic Monitoring of Software - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: arXiv publication_status: submitted related_material: record: - id: '14539' relation: dissertation_contains status: public - id: '14830' relation: later_version status: public status: public title: Learning control policies for stochastic systems with reach-avoid guarantees tmp: image: /images/cc_by_sa.png legal_code_url: https://creativecommons.org/licenses/by-sa/4.0/legalcode name: Creative Commons Attribution-ShareAlike 4.0 International Public License (CC BY-SA 4.0) short: CC BY-SA (4.0) type: preprint user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2022' ... --- _id: '10153' abstract: - lang: eng text: "Gradual typing is a principled means for mixing typed and untyped code. But typed and untyped code often exhibit different programming patterns. There is already substantial research investigating gradually giving types to code exhibiting typical untyped patterns, and some research investigating gradually removing types from code exhibiting typical typed patterns. This paper investigates how to extend these established gradual-typing concepts to give formal guarantees not only about how to change types as code evolves but also about how to change such programming patterns as well.\r\n\r\nIn particular, we explore mixing untyped \"structural\" code with typed \"nominal\" code in an object-oriented language. But whereas previous work only allowed \"nominal\" objects to be treated as \"structural\" objects, we also allow \"structural\" objects to dynamically acquire certain nominal types, namely interfaces. We present a calculus that supports such \"cross-paradigm\" code migration and interoperation in a manner satisfying both the static and dynamic gradual guarantees, and demonstrate that the calculus can be implemented efficiently." acknowledgement: "We thank the reviewers for their valuable suggestions towards improving the paper. We also \r\nthank Mae Milano and Adrian Sampson, as well as the members of the Programming Languages Discussion Group at Cornell University and of the Programming Research Laboratory at Northeastern University, for their helpful feedback on preliminary findings of this work.\r\n\r\nThis material is based upon work supported in part by the National Science Foundation (NSF) through grant CCF-1350182 and the Austrian Science Fund (FWF) through grant Z211-N23 (Wittgenstein~Award).\r\nAny opinions, findings, and conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the NSF or the FWF." article_number: '127' article_processing_charge: No article_type: original author: - first_name: Fabian full_name: Mühlböck, Fabian id: 6395C5F6-89DF-11E9-9C97-6BDFE5697425 last_name: Mühlböck orcid: 0000-0003-1548-0177 - first_name: Ross full_name: Tate, Ross last_name: Tate citation: ama: Mühlböck F, Tate R. Transitioning from structural to nominal code with efficient gradual typing. Proceedings of the ACM on Programming Languages. 2021;5. doi:10.1145/3485504 apa: 'Mühlböck, F., & Tate, R. (2021). Transitioning from structural to nominal code with efficient gradual typing. Proceedings of the ACM on Programming Languages. Chicago, IL, United States: Association for Computing Machinery. https://doi.org/10.1145/3485504' chicago: Mühlböck, Fabian, and Ross Tate. “Transitioning from Structural to Nominal Code with Efficient Gradual Typing.” Proceedings of the ACM on Programming Languages. Association for Computing Machinery, 2021. https://doi.org/10.1145/3485504. ieee: F. Mühlböck and R. Tate, “Transitioning from structural to nominal code with efficient gradual typing,” Proceedings of the ACM on Programming Languages, vol. 5. Association for Computing Machinery, 2021. ista: Mühlböck F, Tate R. 2021. Transitioning from structural to nominal code with efficient gradual typing. Proceedings of the ACM on Programming Languages. 5, 127. mla: Mühlböck, Fabian, and Ross Tate. “Transitioning from Structural to Nominal Code with Efficient Gradual Typing.” Proceedings of the ACM on Programming Languages, vol. 5, 127, Association for Computing Machinery, 2021, doi:10.1145/3485504. short: F. Mühlböck, R. Tate, Proceedings of the ACM on Programming Languages 5 (2021). conference: end_date: 2021-10-23 location: Chicago, IL, United States name: 'OOPSLA: Object-Oriented Programming, Systems, Languages, and Applications' start_date: 2021-10-17 date_created: 2021-10-19T12:48:44Z date_published: 2021-10-15T00:00:00Z date_updated: 2021-11-12T11:30:07Z day: '15' ddc: - '005' department: - _id: ToHe doi: 10.1145/3485504 file: - access_level: open_access checksum: 71011efd2da771cafdec7f0d9693f8c1 content_type: application/pdf creator: fmuehlbo date_created: 2021-10-19T12:52:23Z date_updated: 2021-10-19T12:52:23Z file_id: '10154' file_name: monnom-oopsla21.pdf file_size: 770269 relation: main_file success: 1 file_date_updated: 2021-10-19T12:52:23Z has_accepted_license: '1' intvolume: ' 5' keyword: - gradual typing - gradual guarantee - nominal - structural - call tags language: - iso: eng month: '10' oa: 1 oa_version: Published Version project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Proceedings of the ACM on Programming Languages publication_identifier: eissn: - 2475-1421 publication_status: published publisher: Association for Computing Machinery quality_controlled: '1' status: public title: Transitioning from structural to nominal code with efficient gradual typing tmp: image: /image/cc_by_nd.png legal_code_url: https://creativecommons.org/licenses/by-nd/4.0/legalcode name: Creative Commons Attribution-NoDerivatives 4.0 International (CC BY-ND 4.0) short: CC BY-ND (4.0) type: journal_article user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 volume: 5 year: '2021' ... --- _id: '10669' abstract: - lang: eng text: "We show that Neural ODEs, an emerging class of timecontinuous neural networks, can be verified by solving a set of global-optimization problems. For this purpose, we introduce Stochastic Lagrangian Reachability (SLR), an\r\nabstraction-based technique for constructing a tight Reachtube (an over-approximation of the set of reachable states\r\nover a given time-horizon), and provide stochastic guarantees in the form of confidence intervals for the Reachtube bounds. SLR inherently avoids the infamous wrapping effect (accumulation of over-approximation errors) by performing local optimization steps to expand safe regions instead of repeatedly forward-propagating them as is done by deterministic reachability methods. To enable fast local optimizations, we introduce a novel forward-mode adjoint sensitivity method to compute gradients without the need for backpropagation. Finally, we establish asymptotic and non-asymptotic convergence rates for SLR." acknowledgement: "The authors would like to thank the reviewers for their insightful comments. RH and RG were partially supported by\r\nHorizon-2020 ECSEL Project grant No. 783163 (iDev40). RH was partially supported by Boeing. ML was supported\r\nin part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). SG was funded by FWF\r\nproject W1255-N23. JC was partially supported by NAWA Polish Returns grant PPN/PPO/2018/1/00029. SS was supported by NSF awards DCL-2040599, CCF-1918225, and CPS-1446832.\r\n" alternative_title: - Technical Tracks article_processing_charge: No author: - first_name: Sophie full_name: Grunbacher, Sophie last_name: Grunbacher - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Jacek full_name: Cyranka, Jacek last_name: Cyranka - first_name: Scott A full_name: Smolka, Scott A last_name: Smolka - first_name: Radu full_name: Grosu, Radu last_name: Grosu citation: ama: 'Grunbacher S, Hasani R, Lechner M, Cyranka J, Smolka SA, Grosu R. On the verification of neural ODEs with stochastic guarantees. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol 35. AAAI Press; 2021:11525-11535.' apa: 'Grunbacher, S., Hasani, R., Lechner, M., Cyranka, J., Smolka, S. A., & Grosu, R. (2021). On the verification of neural ODEs with stochastic guarantees. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 11525–11535). Virtual: AAAI Press.' chicago: Grunbacher, Sophie, Ramin Hasani, Mathias Lechner, Jacek Cyranka, Scott A Smolka, and Radu Grosu. “On the Verification of Neural ODEs with Stochastic Guarantees.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:11525–35. AAAI Press, 2021. ieee: S. Grunbacher, R. Hasani, M. Lechner, J. Cyranka, S. A. Smolka, and R. Grosu, “On the verification of neural ODEs with stochastic guarantees,” in Proceedings of the AAAI Conference on Artificial Intelligence, Virtual, 2021, vol. 35, no. 13, pp. 11525–11535. ista: 'Grunbacher S, Hasani R, Lechner M, Cyranka J, Smolka SA, Grosu R. 2021. On the verification of neural ODEs with stochastic guarantees. Proceedings of the AAAI Conference on Artificial Intelligence. AAAI: Association for the Advancement of Artificial Intelligence, Technical Tracks, vol. 35, 11525–11535.' mla: Grunbacher, Sophie, et al. “On the Verification of Neural ODEs with Stochastic Guarantees.” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 13, AAAI Press, 2021, pp. 11525–35. short: S. Grunbacher, R. Hasani, M. Lechner, J. Cyranka, S.A. Smolka, R. Grosu, in:, Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Press, 2021, pp. 11525–11535. conference: end_date: 2021-02-09 location: Virtual name: 'AAAI: Association for the Advancement of Artificial Intelligence' start_date: 2021-02-02 date_created: 2022-01-25T15:47:20Z date_published: 2021-05-28T00:00:00Z date_updated: 2022-05-24T06:33:14Z day: '28' ddc: - '000' department: - _id: GradSch - _id: ToHe external_id: arxiv: - '2012.08863' file: - access_level: open_access checksum: 468d07041e282a1d46ffdae92f709630 content_type: application/pdf creator: mlechner date_created: 2022-01-26T07:38:08Z date_updated: 2022-01-26T07:38:08Z file_id: '10680' file_name: 17372-Article Text-20866-1-2-20210518.pdf file_size: 286906 relation: main_file success: 1 file_date_updated: 2022-01-26T07:38:08Z has_accepted_license: '1' intvolume: ' 35' issue: '13' language: - iso: eng main_file_link: - open_access: '1' url: https://ojs.aaai.org/index.php/AAAI/article/view/17372 month: '05' oa: 1 oa_version: Published Version page: 11525-11535 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Proceedings of the AAAI Conference on Artificial Intelligence publication_identifier: eissn: - 2374-3468 isbn: - 978-1-57735-866-4 issn: - 2159-5399 publication_status: published publisher: AAAI Press quality_controlled: '1' status: public title: On the verification of neural ODEs with stochastic guarantees type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 35 year: '2021' ... --- _id: '10671' abstract: - lang: eng text: We introduce a new class of time-continuous recurrent neural network models. Instead of declaring a learning system’s dynamics by implicit nonlinearities, we construct networks of linear first-order dynamical systems modulated via nonlinear interlinked gates. The resulting models represent dynamical systems with varying (i.e., liquid) time-constants coupled to their hidden state, with outputs being computed by numerical differential equation solvers. These neural networks exhibit stable and bounded behavior, yield superior expressivity within the family of neural ordinary differential equations, and give rise to improved performance on time-series prediction tasks. To demonstrate these properties, we first take a theoretical approach to find bounds over their dynamics, and compute their expressive power by the trajectory length measure in a latent trajectory space. We then conduct a series of time-series prediction experiments to manifest the approximation capability of Liquid Time-Constant Networks (LTCs) compared to classical and modern RNNs. acknowledgement: "R.H. and D.R. are partially supported by Boeing. R.H. and R.G. were partially supported by the Horizon-2020 ECSEL\r\nProject grant No. 783163 (iDev40). M.L. was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). A.A. is supported by the National Science Foundation (NSF) Graduate Research Fellowship Program. This research work is partially drawn from the PhD dissertation of R.H." alternative_title: - Technical Tracks article_processing_charge: No author: - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Alexander full_name: Amini, Alexander last_name: Amini - first_name: Daniela full_name: Rus, Daniela last_name: Rus - first_name: Radu full_name: Grosu, Radu last_name: Grosu citation: ama: 'Hasani R, Lechner M, Amini A, Rus D, Grosu R. Liquid time-constant networks. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol 35. AAAI Press; 2021:7657-7666.' apa: 'Hasani, R., Lechner, M., Amini, A., Rus, D., & Grosu, R. (2021). Liquid time-constant networks. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 7657–7666). Virtual: AAAI Press.' chicago: Hasani, Ramin, Mathias Lechner, Alexander Amini, Daniela Rus, and Radu Grosu. “Liquid Time-Constant Networks.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:7657–66. AAAI Press, 2021. ieee: R. Hasani, M. Lechner, A. Amini, D. Rus, and R. Grosu, “Liquid time-constant networks,” in Proceedings of the AAAI Conference on Artificial Intelligence, Virtual, 2021, vol. 35, no. 9, pp. 7657–7666. ista: 'Hasani R, Lechner M, Amini A, Rus D, Grosu R. 2021. Liquid time-constant networks. Proceedings of the AAAI Conference on Artificial Intelligence. AAAI: Association for the Advancement of Artificial Intelligence, Technical Tracks, vol. 35, 7657–7666.' mla: Hasani, Ramin, et al. “Liquid Time-Constant Networks.” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 9, AAAI Press, 2021, pp. 7657–66. short: R. Hasani, M. Lechner, A. Amini, D. Rus, R. Grosu, in:, Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Press, 2021, pp. 7657–7666. conference: end_date: 2021-02-09 location: Virtual name: 'AAAI: Association for the Advancement of Artificial Intelligence' start_date: 2021-02-02 date_created: 2022-01-25T15:48:36Z date_published: 2021-05-28T00:00:00Z date_updated: 2022-05-24T06:36:54Z day: '28' ddc: - '000' department: - _id: GradSch - _id: ToHe external_id: arxiv: - '2006.04439' file: - access_level: open_access checksum: 0f06995fba06dbcfa7ed965fc66027ff content_type: application/pdf creator: mlechner date_created: 2022-01-26T07:36:03Z date_updated: 2022-01-26T07:36:03Z file_id: '10678' file_name: 16936-Article Text-20430-1-2-20210518 (1).pdf file_size: 4302669 relation: main_file success: 1 file_date_updated: 2022-01-26T07:36:03Z has_accepted_license: '1' intvolume: ' 35' issue: '9' language: - iso: eng main_file_link: - open_access: '1' url: https://ojs.aaai.org/index.php/AAAI/article/view/16936 month: '05' oa: 1 oa_version: Published Version page: 7657-7666 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Proceedings of the AAAI Conference on Artificial Intelligence publication_identifier: eissn: - 2374-3468 isbn: - 978-1-57735-866-4 issn: - 2159-5399 publication_status: published publisher: AAAI Press quality_controlled: '1' status: public title: Liquid time-constant networks type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 35 year: '2021' ... --- _id: '10668' abstract: - lang: eng text: 'Robustness to variations in lighting conditions is a key objective for any deep vision system. To this end, our paper extends the receptive field of convolutional neural networks with two residual components, ubiquitous in the visual processing system of vertebrates: On-center and off-center pathways, with an excitatory center and inhibitory surround; OOCS for short. The On-center pathway is excited by the presence of a light stimulus in its center, but not in its surround, whereas the Off-center pathway is excited by the absence of a light stimulus in its center, but not in its surround. We design OOCS pathways via a difference of Gaussians, with their variance computed analytically from the size of the receptive fields. OOCS pathways complement each other in their response to light stimuli, ensuring this way a strong edge-detection capability, and as a result an accurate and robust inference under challenging lighting conditions. We provide extensive empirical evidence showing that networks supplied with OOCS pathways gain accuracy and illumination-robustness from the novel edge representation, compared to other baselines.' acknowledgement: Z.B. is supported by the Doctoral College Resilient Embedded Systems, which is run jointly by the TU Wien’s Faculty of Informatics and the UAS Technikum Wien. R.G. is partially supported by the Horizon 2020 Era-Permed project Persorad, and ECSEL Project grant no. 783163 (iDev40). R.H and D.R were partially supported by Boeing and MIT. M.L. is supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). alternative_title: - PMLR article_processing_charge: No author: - first_name: Zahra full_name: Babaiee, Zahra last_name: Babaiee - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Daniela full_name: Rus, Daniela last_name: Rus - first_name: Radu full_name: Grosu, Radu last_name: Grosu citation: ama: 'Babaiee Z, Hasani R, Lechner M, Rus D, Grosu R. On-off center-surround receptive fields for accurate and robust image classification. In: Proceedings of the 38th International Conference on Machine Learning. Vol 139. ML Research Press; 2021:478-489.' apa: 'Babaiee, Z., Hasani, R., Lechner, M., Rus, D., & Grosu, R. (2021). On-off center-surround receptive fields for accurate and robust image classification. In Proceedings of the 38th International Conference on Machine Learning (Vol. 139, pp. 478–489). Virtual: ML Research Press.' chicago: Babaiee, Zahra, Ramin Hasani, Mathias Lechner, Daniela Rus, and Radu Grosu. “On-off Center-Surround Receptive Fields for Accurate and Robust Image Classification.” In Proceedings of the 38th International Conference on Machine Learning, 139:478–89. ML Research Press, 2021. ieee: Z. Babaiee, R. Hasani, M. Lechner, D. Rus, and R. Grosu, “On-off center-surround receptive fields for accurate and robust image classification,” in Proceedings of the 38th International Conference on Machine Learning, Virtual, 2021, vol. 139, pp. 478–489. ista: 'Babaiee Z, Hasani R, Lechner M, Rus D, Grosu R. 2021. On-off center-surround receptive fields for accurate and robust image classification. Proceedings of the 38th International Conference on Machine Learning. ML: Machine Learning, PMLR, vol. 139, 478–489.' mla: Babaiee, Zahra, et al. “On-off Center-Surround Receptive Fields for Accurate and Robust Image Classification.” Proceedings of the 38th International Conference on Machine Learning, vol. 139, ML Research Press, 2021, pp. 478–89. short: Z. Babaiee, R. Hasani, M. Lechner, D. Rus, R. Grosu, in:, Proceedings of the 38th International Conference on Machine Learning, ML Research Press, 2021, pp. 478–489. conference: end_date: 2021-07-24 location: Virtual name: 'ML: Machine Learning' start_date: 2021-07-18 date_created: 2022-01-25T15:46:33Z date_published: 2021-07-01T00:00:00Z date_updated: 2022-05-04T15:02:27Z day: '01' ddc: - '000' department: - _id: GradSch - _id: ToHe file: - access_level: open_access checksum: d30eae62561bb517d9f978437d7677db content_type: application/pdf creator: mlechner date_created: 2022-01-26T07:38:32Z date_updated: 2022-01-26T07:38:32Z file_id: '10681' file_name: babaiee21a.pdf file_size: 4246561 relation: main_file success: 1 file_date_updated: 2022-01-26T07:38:32Z has_accepted_license: '1' intvolume: ' 139' language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/3.0/ main_file_link: - open_access: '1' url: https://proceedings.mlr.press/v139/babaiee21a month: '07' oa: 1 oa_version: Published Version page: 478-489 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Proceedings of the 38th International Conference on Machine Learning publication_identifier: issn: - 2640-3498 publication_status: published publisher: ML Research Press quality_controlled: '1' status: public title: On-off center-surround receptive fields for accurate and robust image classification tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: conference user_id: 2EBD1598-F248-11E8-B48F-1D18A9856A87 volume: 139 year: '2021' ... --- _id: '10670' abstract: - lang: eng text: "Imitation learning enables high-fidelity, vision-based learning of policies within rich, photorealistic environments. However, such techniques often rely on traditional discrete-time neural models and face difficulties in generalizing to domain shifts by failing to account for the causal relationships between the agent and the environment. In this paper, we propose a theoretical and experimental framework for learning causal representations using continuous-time neural networks, specifically over their discrete-time counterparts. We evaluate our method in the context of visual-control learning of drones over a series of complex tasks, ranging from short- and long-term navigation, to chasing static and dynamic objects through photorealistic environments. Our results demonstrate that causal continuous-time\r\ndeep models can perform robust navigation tasks, where advanced recurrent models fail. These models learn complex causal control representations directly from raw visual inputs and scale to solve a variety of tasks using imitation learning." acknowledgement: "C.V., R.H. A.A. and D.R. are partially supported by Boeing and MIT. A.A. is supported by the National Science Foundation (NSF) Graduate Research Fellowship Program. M.L. is supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). Research was sponsored by the United States Air Force Research Laboratory and the United States Air Force Artificial Intelligence Accelerator and was accomplished under Cooperative Agreement Number FA8750-19-2-1000. The views and conclusions contained in this document are those of the authors\r\nand should not be interpreted as representing the official policies, either expressed or implied, of the United States Air Force or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation herein.\r\n" alternative_title: - ' Advances in Neural Information Processing Systems' article_processing_charge: No author: - first_name: Charles J full_name: Vorbach, Charles J last_name: Vorbach - first_name: Ramin full_name: Hasani, Ramin last_name: Hasani - first_name: Alexander full_name: Amini, Alexander last_name: Amini - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Daniela full_name: Rus, Daniela last_name: Rus citation: ama: 'Vorbach CJ, Hasani R, Amini A, Lechner M, Rus D. Causal navigation by continuous-time neural networks. In: 35th Conference on Neural Information Processing Systems. ; 2021.' apa: Vorbach, C. J., Hasani, R., Amini, A., Lechner, M., & Rus, D. (2021). Causal navigation by continuous-time neural networks. In 35th Conference on Neural Information Processing Systems. Virtual. chicago: Vorbach, Charles J, Ramin Hasani, Alexander Amini, Mathias Lechner, and Daniela Rus. “Causal Navigation by Continuous-Time Neural Networks.” In 35th Conference on Neural Information Processing Systems, 2021. ieee: C. J. Vorbach, R. Hasani, A. Amini, M. Lechner, and D. Rus, “Causal navigation by continuous-time neural networks,” in 35th Conference on Neural Information Processing Systems, Virtual, 2021. ista: 'Vorbach CJ, Hasani R, Amini A, Lechner M, Rus D. 2021. Causal navigation by continuous-time neural networks. 35th Conference on Neural Information Processing Systems. NeurIPS: Neural Information Processing Systems, Advances in Neural Information Processing Systems, .' mla: Vorbach, Charles J., et al. “Causal Navigation by Continuous-Time Neural Networks.” 35th Conference on Neural Information Processing Systems, 2021. short: C.J. Vorbach, R. Hasani, A. Amini, M. Lechner, D. Rus, in:, 35th Conference on Neural Information Processing Systems, 2021. conference: end_date: 2021-12-10 location: Virtual name: 'NeurIPS: Neural Information Processing Systems' start_date: 2021-12-06 date_created: 2022-01-25T15:47:50Z date_published: 2021-12-01T00:00:00Z date_updated: 2022-01-26T14:33:31Z day: '01' ddc: - '000' department: - _id: GradSch - _id: ToHe external_id: arxiv: - '2106.08314' file: - access_level: open_access checksum: be81f0ade174a8c9b2d4fe09590b2021 content_type: application/pdf creator: mlechner date_created: 2022-01-26T07:37:24Z date_updated: 2022-01-26T07:37:24Z file_id: '10679' file_name: NeurIPS-2021-causal-navigation-by-continuous-time-neural-networks-Paper.pdf file_size: 6841228 relation: main_file success: 1 file_date_updated: 2022-01-26T07:37:24Z has_accepted_license: '1' language: - iso: eng main_file_link: - open_access: '1' url: https://proceedings.neurips.cc/paper/2021/hash/67ba02d73c54f0b83c05507b7fb7267f-Abstract.html month: '12' oa: 1 oa_version: Published Version project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: 35th Conference on Neural Information Processing Systems publication_status: published quality_controlled: '1' status: public title: Causal navigation by continuous-time neural networks tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/3.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported (CC BY-NC-ND 3.0) short: CC BY-NC-ND (3.0) type: conference user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 year: '2021' ... --- _id: '10688' abstract: - lang: eng text: "Civl is a static verifier for concurrent programs designed around the conceptual framework of layered refinement,\r\nwhich views the task of verifying a program as a sequence of program simplification steps each justified by its own invariant. Civl verifies a layered concurrent program that compactly expresses all the programs in this sequence and the supporting invariants. This paper presents the design and implementation of the Civl verifier." acknowledgement: This research was performed while Bernhard Kragl was at IST Austria, supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein Award). alternative_title: - Conference Series article_processing_charge: No author: - first_name: Bernhard full_name: Kragl, Bernhard id: 320FC952-F248-11E8-B48F-1D18A9856A87 last_name: Kragl orcid: 0000-0001-7745-9117 - first_name: Shaz full_name: Qadeer, Shaz last_name: Qadeer citation: ama: 'Kragl B, Qadeer S. The Civl verifier. In: Ruzica P, Whalen MW, eds. Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design. Vol 2. TU Wien Academic Press; 2021:143–152. doi:10.34727/2021/isbn.978-3-85448-046-4_23' apa: 'Kragl, B., & Qadeer, S. (2021). The Civl verifier. In P. Ruzica & M. W. Whalen (Eds.), Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design (Vol. 2, pp. 143–152). Virtual: TU Wien Academic Press. https://doi.org/10.34727/2021/isbn.978-3-85448-046-4_23' chicago: Kragl, Bernhard, and Shaz Qadeer. “The Civl Verifier.” In Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design, edited by Piskac Ruzica and Michael W. Whalen, 2:143–152. TU Wien Academic Press, 2021. https://doi.org/10.34727/2021/isbn.978-3-85448-046-4_23. ieee: B. Kragl and S. Qadeer, “The Civl verifier,” in Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design, Virtual, 2021, vol. 2, pp. 143–152. ista: 'Kragl B, Qadeer S. 2021. The Civl verifier. Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design. FMCAD: Formal Methods in Computer-Aided Design, Conference Series, vol. 2, 143–152.' mla: Kragl, Bernhard, and Shaz Qadeer. “The Civl Verifier.” Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design, edited by Piskac Ruzica and Michael W. Whalen, vol. 2, TU Wien Academic Press, 2021, pp. 143–152, doi:10.34727/2021/isbn.978-3-85448-046-4_23. short: B. Kragl, S. Qadeer, in:, P. Ruzica, M.W. Whalen (Eds.), Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design, TU Wien Academic Press, 2021, pp. 143–152. conference: end_date: 2021-10-22 location: Virtual name: 'FMCAD: Formal Methods in Computer-Aided Design' start_date: 2021-10-20 date_created: 2022-01-26T08:01:30Z date_published: 2021-10-01T00:00:00Z date_updated: 2022-01-26T08:20:41Z day: '01' ddc: - '000' department: - _id: ToHe doi: 10.34727/2021/isbn.978-3-85448-046-4_23 editor: - first_name: Piskac full_name: Ruzica, Piskac last_name: Ruzica - first_name: Michael W. full_name: Whalen, Michael W. last_name: Whalen file: - access_level: open_access checksum: 35438ac9f9750340b7f8ae4ae3220d9f content_type: application/pdf creator: cchlebak date_created: 2022-01-26T08:04:29Z date_updated: 2022-01-26T08:04:29Z file_id: '10689' file_name: 2021_FCAD2021_Kragl.pdf file_size: 390555 relation: main_file success: 1 file_date_updated: 2022-01-26T08:04:29Z has_accepted_license: '1' intvolume: ' 2' language: - iso: eng month: '10' oa: 1 oa_version: Published Version page: 143–152 project: - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize publication: Proceedings of the 21st Conference on Formal Methods in Computer-Aided Design publication_identifier: isbn: - 978-3-85448-046-4 publication_status: published publisher: TU Wien Academic Press quality_controlled: '1' status: public title: The Civl verifier tmp: image: /images/cc_by.png legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0) short: CC BY (4.0) type: conference user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9 volume: 2 year: '2021' ... --- _id: '9281' abstract: - lang: eng text: We comment on two formal proofs of Fermat's sum of two squares theorem, written using the Mathematical Components libraries of the Coq proof assistant. The first one follows Zagier's celebrated one-sentence proof; the second follows David Christopher's recent new proof relying on partition-theoretic arguments. Both formal proofs rely on a general property of involutions of finite sets, of independent interest. The proof technique consists for the most part of automating recurrent tasks (such as case distinctions and computations on natural numbers) via ad hoc tactics. article_number: '2103.11389' article_processing_charge: No author: - first_name: Guillaume full_name: Dubach, Guillaume id: D5C6A458-10C4-11EA-ABF4-A4B43DDC885E last_name: Dubach orcid: 0000-0001-6892-8137 - first_name: Fabian full_name: Mühlböck, Fabian id: 6395C5F6-89DF-11E9-9C97-6BDFE5697425 last_name: Mühlböck orcid: 0000-0003-1548-0177 citation: ama: Dubach G, Mühlböck F. Formal verification of Zagier’s one-sentence proof. arXiv. doi:10.48550/arXiv.2103.11389 apa: Dubach, G., & Mühlböck, F. (n.d.). Formal verification of Zagier’s one-sentence proof. arXiv. https://doi.org/10.48550/arXiv.2103.11389 chicago: Dubach, Guillaume, and Fabian Mühlböck. “Formal Verification of Zagier’s One-Sentence Proof.” ArXiv, n.d. https://doi.org/10.48550/arXiv.2103.11389. ieee: G. Dubach and F. Mühlböck, “Formal verification of Zagier’s one-sentence proof,” arXiv. . ista: Dubach G, Mühlböck F. Formal verification of Zagier’s one-sentence proof. arXiv, 2103.11389. mla: Dubach, Guillaume, and Fabian Mühlböck. “Formal Verification of Zagier’s One-Sentence Proof.” ArXiv, 2103.11389, doi:10.48550/arXiv.2103.11389. short: G. Dubach, F. Mühlböck, ArXiv (n.d.). date_created: 2021-03-23T05:38:48Z date_published: 2021-03-21T00:00:00Z date_updated: 2023-05-03T10:26:45Z day: '21' department: - _id: LaEr - _id: ToHe doi: 10.48550/arXiv.2103.11389 ec_funded: 1 external_id: arxiv: - '2103.11389' language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/2103.11389 month: '03' oa: 1 oa_version: Preprint project: - _id: 260C2330-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '754411' name: ISTplus - Postdoctoral Fellowships publication: arXiv publication_status: submitted related_material: record: - id: '9946' relation: other status: public status: public title: Formal verification of Zagier's one-sentence proof type: preprint user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 year: '2021' ... --- _id: '10665' abstract: - lang: eng text: "Formal verification of neural networks is an active topic of research, and recent advances have significantly increased the size of the networks that verification tools can handle. However, most methods are designed for verification of an idealized model of the actual network which works over real arithmetic and ignores rounding imprecisions. This idealization is in stark contrast to network quantization, which is a technique that trades numerical precision for computational efficiency and is, therefore, often applied in practice. Neglecting rounding errors of such low-bit quantized neural networks has been shown to lead to wrong conclusions about the network’s correctness. Thus, the desired approach for verifying quantized neural networks would be one that takes these rounding errors\r\ninto account. In this paper, we show that verifying the bitexact implementation of quantized neural networks with bitvector specifications is PSPACE-hard, even though verifying idealized real-valued networks and satisfiability of bit-vector specifications alone are each in NP. Furthermore, we explore several practical heuristics toward closing the complexity gap between idealized and bit-exact verification. In particular, we propose three techniques for making SMT-based verification of quantized neural networks more scalable. Our experiments demonstrate that our proposed methods allow a speedup of up to three orders of magnitude over existing approaches." acknowledgement: "This research was supported in part by the Austrian Science Fund (FWF) under grant Z211-N23 (Wittgenstein\r\nAward), ERC CoG 863818 (FoRM-SMArt), and the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.\r\n" alternative_title: - Technical Tracks article_processing_charge: No author: - first_name: Thomas A full_name: Henzinger, Thomas A id: 40876CD8-F248-11E8-B48F-1D18A9856A87 last_name: Henzinger orcid: 0000-0002-2985-7724 - first_name: Mathias full_name: Lechner, Mathias id: 3DC22916-F248-11E8-B48F-1D18A9856A87 last_name: Lechner - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic citation: ama: 'Henzinger TA, Lechner M, Zikelic D. Scalable verification of quantized neural networks. In: Proceedings of the AAAI Conference on Artificial Intelligence. Vol 35. AAAI Press; 2021:3787-3795.' apa: 'Henzinger, T. A., Lechner, M., & Zikelic, D. (2021). Scalable verification of quantized neural networks. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 35, pp. 3787–3795). Virtual: AAAI Press.' chicago: Henzinger, Thomas A, Mathias Lechner, and Dorde Zikelic. “Scalable Verification of Quantized Neural Networks.” In Proceedings of the AAAI Conference on Artificial Intelligence, 35:3787–95. AAAI Press, 2021. ieee: T. A. Henzinger, M. Lechner, and D. Zikelic, “Scalable verification of quantized neural networks,” in Proceedings of the AAAI Conference on Artificial Intelligence, Virtual, 2021, vol. 35, no. 5A, pp. 3787–3795. ista: 'Henzinger TA, Lechner M, Zikelic D. 2021. Scalable verification of quantized neural networks. Proceedings of the AAAI Conference on Artificial Intelligence. AAAI: Association for the Advancement of Artificial Intelligence, Technical Tracks, vol. 35, 3787–3795.' mla: Henzinger, Thomas A., et al. “Scalable Verification of Quantized Neural Networks.” Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 5A, AAAI Press, 2021, pp. 3787–95. short: T.A. Henzinger, M. Lechner, D. Zikelic, in:, Proceedings of the AAAI Conference on Artificial Intelligence, AAAI Press, 2021, pp. 3787–3795. conference: end_date: 2021-02-09 location: Virtual name: 'AAAI: Association for the Advancement of Artificial Intelligence' start_date: 2021-02-02 date_created: 2022-01-25T15:15:02Z date_published: 2021-05-28T00:00:00Z date_updated: 2023-06-23T07:01:11Z day: '28' ddc: - '000' department: - _id: GradSch - _id: ToHe ec_funded: 1 external_id: arxiv: - '2012.08185' file: - access_level: open_access checksum: 2bc8155b2526a70fba5b7301bc89dbd1 content_type: application/pdf creator: mlechner date_created: 2022-01-26T07:41:16Z date_updated: 2022-01-26T07:41:16Z file_id: '10684' file_name: 16496-Article Text-19990-1-2-20210518 (1).pdf file_size: 137235 relation: main_file success: 1 file_date_updated: 2022-01-26T07:41:16Z has_accepted_license: '1' intvolume: ' 35' issue: 5A language: - iso: eng main_file_link: - open_access: '1' url: https://ojs.aaai.org/index.php/AAAI/article/view/16496 month: '05' oa: 1 oa_version: Published Version page: 3787-3795 project: - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program - _id: 25F42A32-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: Z211 name: The Wittgenstein Prize - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' publication: Proceedings of the AAAI Conference on Artificial Intelligence publication_identifier: eissn: - 2374-3468 isbn: - 978-1-57735-866-4 issn: - 2159-5399 publication_status: published publisher: AAAI Press quality_controlled: '1' related_material: record: - id: '11362' relation: dissertation_contains status: public scopus_import: '1' status: public title: Scalable verification of quantized neural networks type: conference user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87 volume: 35 year: '2021' ...