--- _id: '11459' abstract: - lang: eng text: 'We present a novel approach to differential cost analysis that, given a program revision, attempts to statically bound the difference in resource usage, or cost, between the two program versions. Differential cost analysis is particularly interesting because of the many compelling applications for it, such as detecting resource-use regressions at code-review time or proving the absence of certain side-channel vulnerabilities. One prior approach to differential cost analysis is to apply relational reasoning that conceptually constructs a product program on which one can over-approximate the difference in costs between the two program versions. However, a significant challenge in any relational approach is effectively aligning the program versions to get precise results. In this paper, our key insight is that we can avoid the need for and the limitations of program alignment if, instead, we bound the difference of two cost-bound summaries rather than directly bounding the concrete cost difference. In particular, our method computes a threshold value for the maximal difference in cost between two program versions simultaneously using two kinds of cost-bound summaries---a potential function that evaluates to an upper bound for the cost incurred in the first program and an anti-potential function that evaluates to a lower bound for the cost incurred in the second. Our method has a number of desirable properties: it can be fully automated, it allows optimizing the threshold value on relative cost, it is suitable for programs that are not syntactically similar, and it supports non-determinism. We have evaluated an implementation of our approach on a number of program pairs collected from the literature, and we find that our method computes tight threshold values on relative cost in most examples.' acknowledgement: "We thank Shaun Willows, Thomas Lugnet, and the Living Room Application Vending team for suggesting threshold\r\nbounds as a developer-friendly way to interact with a differential cost analyzer, and we thank Jim Christy, Daniel\r\nSchoepe, and the Prime Video Automated Reasoning team for their support and helpful suggestions throughout the\r\nproject. We also thank Michael Emmi for feedback on an earlier version of this paper. And finally, we thank the anonymous reviewers for their useful feedback and Aws Albarghouthi for shepherding the final version of the paper. Ðorđe Žikelić was also partially supported by ERC CoG 863818 (FoRM-SMArt)." article_processing_charge: No author: - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic - first_name: Bor-Yuh Evan full_name: Chang, Bor-Yuh Evan last_name: Chang - first_name: Pauline full_name: Bolignano, Pauline last_name: Bolignano - first_name: Franco full_name: Raimondi, Franco last_name: Raimondi citation: ama: 'Zikelic D, Chang B-YE, Bolignano P, Raimondi F. Differential cost analysis with simultaneous potentials and anti-potentials. In: Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation. Association for Computing Machinery; 2022:442-457. doi:10.1145/3519939.3523435' apa: 'Zikelic, D., Chang, B.-Y. E., Bolignano, P., & Raimondi, F. (2022). Differential cost analysis with simultaneous potentials and anti-potentials. In Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation (pp. 442–457). San Diego, CA, United States: Association for Computing Machinery. https://doi.org/10.1145/3519939.3523435' chicago: Zikelic, Dorde, Bor-Yuh Evan Chang, Pauline Bolignano, and Franco Raimondi. “Differential Cost Analysis with Simultaneous Potentials and Anti-Potentials.” In Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation, 442–57. Association for Computing Machinery, 2022. https://doi.org/10.1145/3519939.3523435. ieee: D. Zikelic, B.-Y. E. Chang, P. Bolignano, and F. Raimondi, “Differential cost analysis with simultaneous potentials and anti-potentials,” in Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation, San Diego, CA, United States, 2022, pp. 442–457. ista: 'Zikelic D, Chang B-YE, Bolignano P, Raimondi F. 2022. Differential cost analysis with simultaneous potentials and anti-potentials. Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation. PLDI: Programming Language Design and Implementation, 442–457.' mla: Zikelic, Dorde, et al. “Differential Cost Analysis with Simultaneous Potentials and Anti-Potentials.” Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation, Association for Computing Machinery, 2022, pp. 442–57, doi:10.1145/3519939.3523435. short: D. Zikelic, B.-Y.E. Chang, P. Bolignano, F. Raimondi, in:, Proceedings of the 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation, Association for Computing Machinery, 2022, pp. 442–457. conference: end_date: 2022-06-17 location: San Diego, CA, United States name: 'PLDI: Programming Language Design and Implementation' start_date: 2022-06-13 date_created: 2022-06-21T09:26:15Z date_published: 2022-06-09T00:00:00Z date_updated: 2023-08-03T07:22:33Z day: '09' ddc: - '000' department: - _id: GradSch - _id: KrCh doi: 10.1145/3519939.3523435 ec_funded: 1 external_id: arxiv: - '2204.00870' isi: - '000850435600030' file: - access_level: open_access checksum: 7eb915a2ca5b5ce4729321f33b2e16e1 content_type: application/pdf creator: dernst date_created: 2022-06-27T07:38:21Z date_updated: 2022-06-27T07:38:21Z file_id: '11466' file_name: 2022_PLDI_Zikelic.pdf file_size: 318697 relation: main_file success: 1 file_date_updated: 2022-06-27T07:38:21Z has_accepted_license: '1' isi: 1 language: - iso: eng license: https://creativecommons.org/licenses/by-nc-nd/4.0/ month: '06' oa: 1 oa_version: Published Version page: 442-457 project: - _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 43rd ACM SIGPLAN International Conference on Programming Language Design and Implementation publication_identifier: isbn: - '9781450392655' publication_status: published publisher: Association for Computing Machinery quality_controlled: '1' scopus_import: '1' status: public title: Differential cost analysis with simultaneous potentials and anti-potentials tmp: image: /images/cc_by_nc_nd.png legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) short: CC BY-NC-ND (4.0) type: conference user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 year: '2022' ... --- _id: '12257' abstract: - lang: eng text: Structural balance theory is an established framework for studying social relationships of friendship and enmity. These relationships are modeled by a signed network whose energy potential measures the level of imbalance, while stochastic dynamics drives the network toward a state of minimum energy that captures social balance. It is known that this energy landscape has local minima that can trap socially aware dynamics, preventing it from reaching balance. Here we first study the robustness and attractor properties of these local minima. We show that a stochastic process can reach them from an abundance of initial states and that some local minima cannot be escaped by mild perturbations of the network. Motivated by these anomalies, we introduce best-edge dynamics (BED), a new plausible stochastic process. We prove that BED always reaches balance and that it does so fast in various interesting settings. acknowledgement: "K.C. acknowledges support from ERC Start Grant No. (279307: Graph Games), ERC Consolidator Grant No. (863818: ForM-SMart), and Austrian Science Fund (FWF)\r\nGrants No. P23499-N23 and No. S11407-N23 (RiSE). This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie\r\nSkłodowska-Curie Grant Agreement No. 665385." article_number: '034321' article_processing_charge: No article_type: original author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Jakub full_name: Svoboda, Jakub id: 130759D2-D7DD-11E9-87D2-DE0DE6697425 last_name: Svoboda - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic - first_name: Andreas full_name: Pavlogiannis, Andreas id: 49704004-F248-11E8-B48F-1D18A9856A87 last_name: Pavlogiannis orcid: 0000-0002-8943-0722 - first_name: Josef full_name: Tkadlec, Josef id: 3F24CCC8-F248-11E8-B48F-1D18A9856A87 last_name: Tkadlec orcid: 0000-0002-1097-9684 citation: ama: 'Chatterjee K, Svoboda J, Zikelic D, Pavlogiannis A, Tkadlec J. Social balance on networks: Local minima and best-edge dynamics. Physical Review E. 2022;106(3). doi:10.1103/physreve.106.034321' apa: 'Chatterjee, K., Svoboda, J., Zikelic, D., Pavlogiannis, A., & Tkadlec, J. (2022). Social balance on networks: Local minima and best-edge dynamics. Physical Review E. American Physical Society. https://doi.org/10.1103/physreve.106.034321' chicago: 'Chatterjee, Krishnendu, Jakub Svoboda, Dorde Zikelic, Andreas Pavlogiannis, and Josef Tkadlec. “Social Balance on Networks: Local Minima and Best-Edge Dynamics.” Physical Review E. American Physical Society, 2022. https://doi.org/10.1103/physreve.106.034321.' ieee: 'K. Chatterjee, J. Svoboda, D. Zikelic, A. Pavlogiannis, and J. Tkadlec, “Social balance on networks: Local minima and best-edge dynamics,” Physical Review E, vol. 106, no. 3. American Physical Society, 2022.' ista: 'Chatterjee K, Svoboda J, Zikelic D, Pavlogiannis A, Tkadlec J. 2022. Social balance on networks: Local minima and best-edge dynamics. Physical Review E. 106(3), 034321.' mla: 'Chatterjee, Krishnendu, et al. “Social Balance on Networks: Local Minima and Best-Edge Dynamics.” Physical Review E, vol. 106, no. 3, 034321, American Physical Society, 2022, doi:10.1103/physreve.106.034321.' short: K. Chatterjee, J. Svoboda, D. Zikelic, A. Pavlogiannis, J. Tkadlec, Physical Review E 106 (2022). date_created: 2023-01-16T09:57:57Z date_published: 2022-09-29T00:00:00Z date_updated: 2023-08-04T09:50:44Z day: '29' department: - _id: KrCh doi: 10.1103/physreve.106.034321 ec_funded: 1 external_id: arxiv: - '2210.02394' isi: - '000870243100001' intvolume: ' 106' isi: 1 issue: '3' language: - iso: eng main_file_link: - open_access: '1' url: https://doi.org/10.48550/arXiv.2210.02394 month: '09' oa: 1 oa_version: Preprint project: - _id: 2581B60A-B435-11E9-9278-68D0E5697425 call_identifier: FP7 grant_number: '279307' name: 'Quantitative Graph Games: Theory and Applications' - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' - _id: 2584A770-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: P 23499-N23 name: Modern Graph Algorithmic Techniques in Formal Verification - _id: 25863FF4-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S11407 name: Game Theory - _id: 2564DBCA-B435-11E9-9278-68D0E5697425 call_identifier: H2020 grant_number: '665385' name: International IST Doctoral Program publication: Physical Review E publication_identifier: eissn: - 2470-0053 issn: - 2470-0045 publication_status: published publisher: American Physical Society quality_controlled: '1' scopus_import: '1' status: public title: 'Social balance on networks: Local minima and best-edge dynamics' type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 106 year: '2022' ... --- _id: '12280' abstract: - lang: eng text: 'In repeated interactions, players can use strategies that respond to the outcome of previous rounds. Much of the existing literature on direct reciprocity assumes that all competing individuals use the same strategy space. Here, we study both learning and evolutionary dynamics of players that differ in the strategy space they explore. We focus on the infinitely repeated donation game and compare three natural strategy spaces: memory-1 strategies, which consider the last moves of both players, reactive strategies, which respond to the last move of the co-player, and unconditional strategies. These three strategy spaces differ in the memory capacity that is needed. We compute the long term average payoff that is achieved in a pairwise learning process. We find that smaller strategy spaces can dominate larger ones. For weak selection, unconditional players dominate both reactive and memory-1 players. For intermediate selection, reactive players dominate memory-1 players. Only for strong selection and low cost-to-benefit ratio, memory-1 players dominate the others. We observe that the supergame between strategy spaces can be a social dilemma: maximum payoff is achieved if both players explore a larger strategy space, but smaller strategy spaces dominate.' acknowledgement: "This work was supported by the European Research Council (https://erc.europa.eu/)\r\nCoG 863818 (ForM-SMArt) (to K.C.), and the European Research Council Starting Grant 850529: E-DIRECT (to C.H.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript." article_number: e1010149 article_processing_charge: No article_type: original author: - first_name: Laura full_name: Schmid, Laura id: 38B437DE-F248-11E8-B48F-1D18A9856A87 last_name: Schmid orcid: 0000-0002-6978-7329 - first_name: Christian full_name: Hilbe, Christian id: 2FDF8F3C-F248-11E8-B48F-1D18A9856A87 last_name: Hilbe orcid: 0000-0001-5116-955X - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Martin full_name: Nowak, Martin last_name: Nowak citation: ama: Schmid L, Hilbe C, Chatterjee K, Nowak M. Direct reciprocity between individuals that use different strategy spaces. PLOS Computational Biology. 2022;18(6). doi:10.1371/journal.pcbi.1010149 apa: Schmid, L., Hilbe, C., Chatterjee, K., & Nowak, M. (2022). Direct reciprocity between individuals that use different strategy spaces. PLOS Computational Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1010149 chicago: Schmid, Laura, Christian Hilbe, Krishnendu Chatterjee, and Martin Nowak. “Direct Reciprocity between Individuals That Use Different Strategy Spaces.” PLOS Computational Biology. Public Library of Science, 2022. https://doi.org/10.1371/journal.pcbi.1010149. ieee: L. Schmid, C. Hilbe, K. Chatterjee, and M. Nowak, “Direct reciprocity between individuals that use different strategy spaces,” PLOS Computational Biology, vol. 18, no. 6. Public Library of Science, 2022. ista: Schmid L, Hilbe C, Chatterjee K, Nowak M. 2022. Direct reciprocity between individuals that use different strategy spaces. PLOS Computational Biology. 18(6), e1010149. mla: Schmid, Laura, et al. “Direct Reciprocity between Individuals That Use Different Strategy Spaces.” PLOS Computational Biology, vol. 18, no. 6, e1010149, Public Library of Science, 2022, doi:10.1371/journal.pcbi.1010149. short: L. Schmid, C. Hilbe, K. Chatterjee, M. Nowak, PLOS Computational Biology 18 (2022). date_created: 2023-01-16T10:02:51Z date_published: 2022-06-14T00:00:00Z date_updated: 2023-08-04T10:27:08Z day: '14' ddc: - '000' - '570' department: - _id: KrCh doi: 10.1371/journal.pcbi.1010149 ec_funded: 1 external_id: isi: - '000843626800031' pmid: - '35700167' file: - access_level: open_access checksum: 31b6b311b6731f1658277a9dfff6632c content_type: application/pdf creator: dernst date_created: 2023-01-30T11:28:13Z date_updated: 2023-01-30T11:28:13Z file_id: '12460' file_name: 2022_PlosCompBio_Schmid.pdf file_size: 3143222 relation: main_file success: 1 file_date_updated: 2023-01-30T11:28:13Z has_accepted_license: '1' intvolume: ' 18' isi: 1 issue: '6' keyword: - Computational Theory and Mathematics - Cellular and Molecular Neuroscience - Genetics - Molecular Biology - Ecology - Modeling and Simulation - Ecology - Evolution - Behavior and Systematics language: - iso: eng license: https://creativecommons.org/licenses/by/4.0/ month: '06' oa: 1 oa_version: Published Version pmid: 1 project: - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' publication: PLOS Computational Biology publication_identifier: eissn: - 1553-7358 publication_status: published publisher: Public Library of Science quality_controlled: '1' scopus_import: '1' status: public title: Direct reciprocity between individuals that use different strategy spaces 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: 18 year: '2022' ... --- _id: '9311' abstract: - lang: eng text: 'Partially observable Markov decision processes (POMDPs) are standard models for dynamic systems with probabilistic and nondeterministic behaviour in uncertain environments. We prove that in POMDPs with long-run average objective, the decision maker has approximately optimal strategies with finite memory. This implies notably that approximating the long-run value is recursively enumerable, as well as a weak continuity property of the value with respect to the transition function. ' acknowledgement: "Partially supported by Austrian Science Fund (FWF) NFN Grant No RiSE/SHiNE S11407, by CONICYT Chile through grant PII 20150140, and by ECOS-CONICYT through grant C15E03.\r\n" article_processing_charge: No article_type: original author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Raimundo J full_name: Saona Urmeneta, Raimundo J id: BD1DF4C4-D767-11E9-B658-BC13E6697425 last_name: Saona Urmeneta orcid: 0000-0001-5103-038X - first_name: Bruno full_name: Ziliotto, Bruno last_name: Ziliotto citation: ama: Chatterjee K, Saona Urmeneta RJ, Ziliotto B. Finite-memory strategies in POMDPs with long-run average objectives. Mathematics of Operations Research. 2022;47(1):100-119. doi:10.1287/moor.2020.1116 apa: Chatterjee, K., Saona Urmeneta, R. J., & Ziliotto, B. (2022). Finite-memory strategies in POMDPs with long-run average objectives. Mathematics of Operations Research. Institute for Operations Research and the Management Sciences. https://doi.org/10.1287/moor.2020.1116 chicago: Chatterjee, Krishnendu, Raimundo J Saona Urmeneta, and Bruno Ziliotto. “Finite-Memory Strategies in POMDPs with Long-Run Average Objectives.” Mathematics of Operations Research. Institute for Operations Research and the Management Sciences, 2022. https://doi.org/10.1287/moor.2020.1116. ieee: K. Chatterjee, R. J. Saona Urmeneta, and B. Ziliotto, “Finite-memory strategies in POMDPs with long-run average objectives,” Mathematics of Operations Research, vol. 47, no. 1. Institute for Operations Research and the Management Sciences, pp. 100–119, 2022. ista: Chatterjee K, Saona Urmeneta RJ, Ziliotto B. 2022. Finite-memory strategies in POMDPs with long-run average objectives. Mathematics of Operations Research. 47(1), 100–119. mla: Chatterjee, Krishnendu, et al. “Finite-Memory Strategies in POMDPs with Long-Run Average Objectives.” Mathematics of Operations Research, vol. 47, no. 1, Institute for Operations Research and the Management Sciences, 2022, pp. 100–19, doi:10.1287/moor.2020.1116. short: K. Chatterjee, R.J. Saona Urmeneta, B. Ziliotto, Mathematics of Operations Research 47 (2022) 100–119. date_created: 2021-04-08T09:33:31Z date_published: 2022-02-01T00:00:00Z date_updated: 2023-09-05T13:16:11Z day: '01' department: - _id: GradSch - _id: KrCh doi: 10.1287/moor.2020.1116 external_id: arxiv: - '1904.13360' isi: - '000731918100001' intvolume: ' 47' isi: 1 issue: '1' keyword: - Management Science and Operations Research - General Mathematics - Computer Science Applications language: - iso: eng main_file_link: - open_access: '1' url: https://arxiv.org/abs/1904.13360 month: '02' oa: 1 oa_version: Preprint page: 100-119 project: - _id: 25863FF4-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S11407 name: Game Theory publication: Mathematics of Operations Research publication_identifier: eissn: - 1526-5471 issn: - 0364-765X publication_status: published publisher: Institute for Operations Research and the Management Sciences quality_controlled: '1' scopus_import: '1' status: public title: Finite-memory strategies in POMDPs with long-run average objectives type: journal_article user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 47 year: '2022' ... --- _id: '12170' abstract: - lang: eng text: We present PET, a specialized and highly optimized framework for partial exploration on probabilistic systems. Over the last decade, several significant advances in the analysis of Markov decision processes employed partial exploration. In a nutshell, this idea allows to focus computation on specific parts of the system, guided by heuristics, while maintaining correctness. In particular, only relevant parts of the system are constructed on demand, which in turn potentially allows to omit constructing large parts of the system. Depending on the model, this leads to dramatic speed-ups, in extreme cases even up to an arbitrary factor. PET unifies several previous implementations and provides a flexible framework to easily implement partial exploration for many further problems. Our experimental evaluation shows significant improvements compared to the previous implementations while vastly reducing the overhead required to add support for additional properties. acknowledgement: We thank Pranav Ashok and Maximilian Weininger for their contributions to spiritual predecessors of PET as well as motivating the initial development of this tool. alternative_title: - LNCS article_processing_charge: No author: - first_name: Tobias full_name: Meggendorfer, Tobias id: b21b0c15-30a2-11eb-80dc-f13ca25802e1 last_name: Meggendorfer orcid: 0000-0002-1712-2165 citation: ama: 'Meggendorfer T. PET – A partial exploration tool for probabilistic verification. In: 20th International Symposium on Automated Technology for Verification and Analysis. Vol 13505. Springer Nature; 2022:320-326. doi:10.1007/978-3-031-19992-9_20' apa: 'Meggendorfer, T. (2022). PET – A partial exploration tool for probabilistic verification. In 20th International Symposium on Automated Technology for Verification and Analysis (Vol. 13505, pp. 320–326). Virtual: Springer Nature. https://doi.org/10.1007/978-3-031-19992-9_20' chicago: Meggendorfer, Tobias. “PET – A Partial Exploration Tool for Probabilistic Verification.” In 20th International Symposium on Automated Technology for Verification and Analysis, 13505:320–26. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-19992-9_20. ieee: T. Meggendorfer, “PET – A partial exploration tool for probabilistic verification,” in 20th International Symposium on Automated Technology for Verification and Analysis, Virtual, 2022, vol. 13505, pp. 320–326. ista: 'Meggendorfer T. 2022. PET – A partial exploration tool for probabilistic verification. 20th International Symposium on Automated Technology for Verification and Analysis. ATVA: Automated Technology for Verification and Analysis, LNCS, vol. 13505, 320–326.' mla: Meggendorfer, Tobias. “PET – A Partial Exploration Tool for Probabilistic Verification.” 20th International Symposium on Automated Technology for Verification and Analysis, vol. 13505, Springer Nature, 2022, pp. 320–26, doi:10.1007/978-3-031-19992-9_20. short: T. Meggendorfer, in:, 20th International Symposium on Automated Technology for Verification and Analysis, Springer Nature, 2022, pp. 320–326. conference: end_date: 2022-10-28 location: Virtual name: 'ATVA: Automated Technology for Verification and Analysis' start_date: 2022-10-25 date_created: 2023-01-12T12:11:07Z date_published: 2022-10-21T00:00:00Z date_updated: 2023-09-05T15:11:51Z day: '21' department: - _id: KrCh doi: 10.1007/978-3-031-19992-9_20 intvolume: ' 13505' language: - iso: eng month: '10' oa_version: None page: 320-326 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: PET – A partial exploration tool for probabilistic verification type: conference user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1 volume: 13505 year: '2022' ... --- _id: '11402' abstract: - lang: eng text: Fixed-horizon planning considers a weighted graph and asks to construct a path that maximizes the sum of weights for a given time horizon T. However, in many scenarios, the time horizon is not fixed, but the stopping time is chosen according to some distribution such that the expected stopping time is T. If the stopping-time distribution is not known, then to ensure robustness, the distribution is chosen by an adversary as the worst-case scenario. A stationary plan for every vertex always chooses the same outgoing edge. For fixed horizon or fixed stopping-time distribution, stationary plans are not sufficient for optimality. Quite surprisingly we show that when an adversary chooses the stopping-time distribution with expected stopping-time T, then stationary plans are sufficient. While computing optimal stationary plans for fixed horizon is NP-complete, we show that computing optimal stationary plans under adversarial stopping-time distribution can be achieved in polynomial time. acknowledgement: This work was partially supported by Austrian Science Fund (FWF) NFN Grant No RiSE/SHiNE S11407 and by the grant ERC CoG 863818 (ForM-SMArt). article_processing_charge: No article_type: original author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Laurent full_name: Doyen, Laurent last_name: Doyen citation: ama: Chatterjee K, Doyen L. Graph planning with expected finite horizon. Journal of Computer and System Sciences. 2022;129:1-21. doi:10.1016/j.jcss.2022.04.003 apa: Chatterjee, K., & Doyen, L. (2022). Graph planning with expected finite horizon. Journal of Computer and System Sciences. Elsevier. https://doi.org/10.1016/j.jcss.2022.04.003 chicago: Chatterjee, Krishnendu, and Laurent Doyen. “Graph Planning with Expected Finite Horizon.” Journal of Computer and System Sciences. Elsevier, 2022. https://doi.org/10.1016/j.jcss.2022.04.003. ieee: K. Chatterjee and L. Doyen, “Graph planning with expected finite horizon,” Journal of Computer and System Sciences, vol. 129. Elsevier, pp. 1–21, 2022. ista: Chatterjee K, Doyen L. 2022. Graph planning with expected finite horizon. Journal of Computer and System Sciences. 129, 1–21. mla: Chatterjee, Krishnendu, and Laurent Doyen. “Graph Planning with Expected Finite Horizon.” Journal of Computer and System Sciences, vol. 129, Elsevier, 2022, pp. 1–21, doi:10.1016/j.jcss.2022.04.003. short: K. Chatterjee, L. Doyen, Journal of Computer and System Sciences 129 (2022) 1–21. date_created: 2022-05-22T22:01:40Z date_published: 2022-11-01T00:00:00Z date_updated: 2023-09-07T14:48:11Z day: '01' department: - _id: KrCh doi: 10.1016/j.jcss.2022.04.003 ec_funded: 1 external_id: arxiv: - '1802.03642' isi: - '000805002800001' intvolume: ' 129' isi: 1 language: - iso: eng main_file_link: - open_access: '1' url: ' https://doi.org/10.48550/arXiv.1802.03642' month: '11' oa: 1 oa_version: Preprint page: 1-21 project: - _id: 25863FF4-B435-11E9-9278-68D0E5697425 call_identifier: FWF grant_number: S11407 name: Game Theory - _id: 0599E47C-7A3F-11EA-A408-12923DDC885E call_identifier: H2020 grant_number: '863818' name: 'Formal Methods for Stochastic Models: Algorithms and Applications' publication: Journal of Computer and System Sciences publication_identifier: eissn: - 1090-2724 issn: - 0022-0000 publication_status: published publisher: Elsevier quality_controlled: '1' related_material: record: - id: '7402' relation: earlier_version status: public scopus_import: '1' status: public title: Graph planning with expected finite horizon type: journal_article user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8 volume: 129 year: '2022' ... --- _id: '12775' abstract: - lang: eng text: "We consider the problem of approximating the reachability probabilities in Markov decision processes (MDP) with uncountable (continuous) state and action spaces. While there are algorithms that, for special classes of such MDP, provide a sequence of approximations converging to the true value in the limit, our aim is to obtain an algorithm with guarantees on the precision of the approximation.\r\nAs this problem is undecidable in general, assumptions on the MDP are necessary. Our main contribution is to identify sufficient assumptions that are as weak as possible, thus approaching the \"boundary\" of which systems can be correctly and reliably analyzed. To this end, we also argue why each of our assumptions is necessary for algorithms based on processing finitely many observations.\r\nWe present two solution variants. The first one provides converging lower bounds under weaker assumptions than typical ones from previous works concerned with guarantees. The second one then utilizes stronger assumptions to additionally provide converging upper bounds. Altogether, we obtain an anytime algorithm, i.e. yielding a sequence of approximants with known and iteratively improving precision, converging to the true value in the limit. Besides, due to the generality of our assumptions, our algorithms are very general templates, readily allowing for various heuristics from literature in contrast to, e.g., a specific discretization algorithm. Our theoretical contribution thus paves the way for future practical improvements without sacrificing correctness guarantees." acknowledgement: "Kush Grover: The author has been supported by the DFG research training group GRK\r\n2428 ConVeY.\r\nMaximilian Weininger: The author has been partially supported by DFG projects 383882557\r\nStatistical Unbounded Verification (SUV) and 427755713 Group-By Objectives in Probabilistic\r\nVerification (GOPro)" alternative_title: - LIPIcs article_number: '11' article_processing_charge: No author: - first_name: Kush full_name: Grover, Kush last_name: Grover - first_name: Jan full_name: Kretinsky, Jan id: 44CEF464-F248-11E8-B48F-1D18A9856A87 last_name: Kretinsky orcid: 0000-0002-8122-2881 - first_name: Tobias full_name: Meggendorfer, Tobias id: b21b0c15-30a2-11eb-80dc-f13ca25802e1 last_name: Meggendorfer orcid: 0000-0002-1712-2165 - first_name: Maimilian full_name: Weininger, Maimilian last_name: Weininger citation: ama: 'Grover K, Kretinsky J, Meggendorfer T, Weininger M. Anytime guarantees for reachability in uncountable Markov decision processes. In: 33rd International Conference on Concurrency Theory . Vol 243. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022. doi:10.4230/LIPIcs.CONCUR.2022.11' apa: 'Grover, K., Kretinsky, J., Meggendorfer, T., & Weininger, M. (2022). Anytime guarantees for reachability in uncountable Markov decision processes. In 33rd International Conference on Concurrency Theory (Vol. 243). Warsaw, Poland: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2022.11' chicago: Grover, Kush, Jan Kretinsky, Tobias Meggendorfer, and Maimilian Weininger. “Anytime Guarantees for Reachability in Uncountable Markov Decision Processes.” In 33rd International Conference on Concurrency Theory , Vol. 243. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.CONCUR.2022.11. ieee: K. Grover, J. Kretinsky, T. Meggendorfer, and M. Weininger, “Anytime guarantees for reachability in uncountable Markov decision processes,” in 33rd International Conference on Concurrency Theory , Warsaw, Poland, 2022, vol. 243. ista: 'Grover K, Kretinsky J, Meggendorfer T, Weininger M. 2022. Anytime guarantees for reachability in uncountable Markov decision processes. 33rd International Conference on Concurrency Theory . CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 243, 11.' mla: Grover, Kush, et al. “Anytime Guarantees for Reachability in Uncountable Markov Decision Processes.” 33rd International Conference on Concurrency Theory , vol. 243, 11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, doi:10.4230/LIPIcs.CONCUR.2022.11. short: K. Grover, J. Kretinsky, T. Meggendorfer, M. Weininger, in:, 33rd International Conference on Concurrency Theory , Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022. conference: end_date: 2022-09-16 location: Warsaw, Poland name: 'CONCUR: Conference on Concurrency Theory' start_date: 2022-09-13 date_created: 2023-03-28T08:09:32Z date_published: 2022-09-15T00:00:00Z date_updated: 2023-09-26T10:43:30Z day: '15' ddc: - '000' department: - _id: KrCh doi: 10.4230/LIPIcs.CONCUR.2022.11 external_id: arxiv: - '2008.04824' file: - access_level: open_access checksum: e282e43d3ae0ba6e067b72f4583e13c0 content_type: application/pdf creator: dernst date_created: 2023-09-26T10:43:15Z date_updated: 2023-09-26T10:43:15Z file_id: '14372' file_name: 2022_LIPIcS_Grover.pdf file_size: 960036 relation: main_file success: 1 file_date_updated: 2023-09-26T10:43:15Z has_accepted_license: '1' intvolume: ' 243' language: - iso: eng month: '09' oa: 1 oa_version: Published Version publication: '33rd International Conference on Concurrency Theory ' publication_identifier: issn: - 1868-8969 publication_status: published publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik quality_controlled: '1' scopus_import: '1' status: public title: Anytime guarantees for reachability in uncountable Markov decision processes 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: '12000' abstract: - lang: eng text: "We consider the quantitative problem of obtaining lower-bounds on the probability of termination of a given non-deterministic probabilistic program. Specifically, given a non-termination threshold p∈[0,1], we aim for certificates proving that the program terminates with probability at least 1−p. The basic idea of our approach is to find a terminating stochastic invariant, i.e. a subset SI of program states such that (i) the probability of the program ever leaving SI is no more than p, and (ii) almost-surely, the program either leaves SI or terminates.\r\n\r\nWhile stochastic invariants are already well-known, we provide the first proof that the idea above is not only sound, but also complete for quantitative termination analysis. We then introduce a novel sound and complete characterization of stochastic invariants that enables template-based approaches for easy synthesis of quantitative termination certificates, especially in affine or polynomial forms. Finally, by combining this idea with the existing martingale-based methods that are relatively complete for qualitative termination analysis, we obtain the first automated, sound, and relatively complete algorithm for quantitative termination analysis. Notably, our completeness guarantees for quantitative termination analysis are as strong as the best-known methods for the qualitative variant.\r\n\r\nOur prototype implementation demonstrates the effectiveness of our approach on various probabilistic programs. We also demonstrate that our algorithm certifies lower bounds on termination probability for probabilistic programs that are beyond the reach of previous methods." acknowledgement: This research was partially supported by the ERC CoG 863818 (ForM-SMArt), the HKUST-Kaisa Joint Research Institute Project Grant HKJRI3A-055, the HKUST Startup Grant R9272 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: Yes (in subscription journal) author: - first_name: Krishnendu full_name: Chatterjee, Krishnendu id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87 last_name: Chatterjee orcid: 0000-0002-4561-241X - first_name: Amir Kafshdar full_name: Goharshady, Amir Kafshdar id: 391365CE-F248-11E8-B48F-1D18A9856A87 last_name: Goharshady orcid: 0000-0003-1702-6584 - first_name: Tobias full_name: Meggendorfer, Tobias id: b21b0c15-30a2-11eb-80dc-f13ca25802e1 last_name: Meggendorfer orcid: 0000-0002-1712-2165 - first_name: Dorde full_name: Zikelic, Dorde id: 294AA7A6-F248-11E8-B48F-1D18A9856A87 last_name: Zikelic orcid: 0000-0002-4681-1699 citation: ama: 'Chatterjee K, Goharshady AK, Meggendorfer T, Zikelic D. Sound and complete certificates for auantitative termination analysis of probabilistic programs. In: Proceedings of the 34th International Conference on Computer Aided Verification. Vol 13371. Springer; 2022:55-78. doi:10.1007/978-3-031-13185-1_4' apa: 'Chatterjee, K., Goharshady, A. K., Meggendorfer, T., & Zikelic, D. (2022). Sound and complete certificates for auantitative termination analysis of probabilistic programs. In Proceedings of the 34th International Conference on Computer Aided Verification (Vol. 13371, pp. 55–78). Haifa, Israel: Springer. https://doi.org/10.1007/978-3-031-13185-1_4' chicago: Chatterjee, Krishnendu, Amir Kafshdar Goharshady, Tobias Meggendorfer, and Dorde Zikelic. “Sound and Complete Certificates for Auantitative Termination Analysis of Probabilistic Programs.” In Proceedings of the 34th International Conference on Computer Aided Verification, 13371:55–78. Springer, 2022. https://doi.org/10.1007/978-3-031-13185-1_4. ieee: K. Chatterjee, A. K. Goharshady, T. Meggendorfer, and D. Zikelic, “Sound and complete certificates for auantitative termination analysis of probabilistic programs,” in Proceedings of the 34th International Conference on Computer Aided Verification, Haifa, Israel, 2022, vol. 13371, pp. 55–78. ista: 'Chatterjee K, Goharshady AK, Meggendorfer T, Zikelic D. 2022. Sound and complete certificates for auantitative termination analysis of probabilistic programs. Proceedings of the 34th International Conference on Computer Aided Verification. CAV: Computer Aided Verification, LNCS, vol. 13371, 55–78.' mla: Chatterjee, Krishnendu, et al. “Sound and Complete Certificates for Auantitative Termination Analysis of Probabilistic Programs.” Proceedings of the 34th International Conference on Computer Aided Verification, vol. 13371, Springer, 2022, pp. 55–78, doi:10.1007/978-3-031-13185-1_4. short: K. Chatterjee, A.K. Goharshady, T. Meggendorfer, D. Zikelic, in:, Proceedings of the 34th International Conference on Computer Aided Verification, Springer, 2022, pp. 55–78. conference: end_date: 2022-08-10 location: Haifa, Israel name: 'CAV: Computer Aided Verification' start_date: 2022-08-07 date_created: 2022-08-28T22:02:02Z date_published: 2022-08-07T00:00:00Z date_updated: 2023-11-30T10:55:37Z day: '07' ddc: - '000' department: - _id: KrCh doi: 10.1007/978-3-031-13185-1_4 ec_funded: 1 external_id: isi: - '000870304500004' file: - access_level: open_access checksum: 24e0f810ec52735a90ade95198bc641d content_type: application/pdf creator: alisjak date_created: 2022-08-29T09:17:01Z date_updated: 2022-08-29T09:17:01Z file_id: '12003' file_name: 2022_LNCS_Chatterjee.pdf file_size: 505094 relation: main_file success: 1 file_date_updated: 2022-08-29T09:17:01Z has_accepted_license: '1' intvolume: ' 13371' isi: 1 language: - iso: eng month: '08' oa: 1 oa_version: Published Version page: 55-78 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 34th International Conference on Computer Aided Verification publication_identifier: eissn: - 1611-3349 isbn: - '9783031131844' issn: - 0302-9743 publication_status: published publisher: Springer quality_controlled: '1' related_material: record: - id: '14539' relation: dissertation_contains status: public scopus_import: '1' status: public title: Sound and complete certificates for auantitative termination analysis of probabilistic programs 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: 13371 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' ...