---
_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:
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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:
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publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Phenotype control of partially specified boolean networks
tmp:
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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:
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checksum: 1a361d83db0244fd32c03b544c294b5a
content_type: application/pdf
creator: dernst
date_created: 2024-01-09T10:01:07Z
date_updated: 2024-01-09T10:01:07Z
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file_name: 2023_LNCSCAV_Majumdar.pdf
file_size: 405147
relation: main_file
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intvolume: ' 13966'
language:
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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:
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publication_status: published
publisher: Springer Nature
quality_controlled: '1'
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title: A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties
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...
---
_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:
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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:
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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:
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relation: research_data
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status: public
title: Monitoring hyperproperties with prefix transducers
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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
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title: Closed-form continuous-time neural networks
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