---
_id: '14758'
abstract:
- lang: eng
  text: 'We present a flexible and efficient toolchain to symbolically solve (standard)
    Rabin games, fair-adversarial Rabin games, and 2 1/2 license type-player Rabin
    games. To our best knowledge, our tools are the first ones to be able to solve
    these problems. Furthermore, using these flexible game solvers as a back-end,
    we implemented a tool for computing correct-by-construction controllers for stochastic
    dynamical systems under LTL specifications. Our implementations use the recent
    theoretical result that all of these games can be solved using the same symbolic
    fixpoint algorithm but utilizing different, domain specific calculations of the
    involved predecessor operators. The main feature of our toolchain is the utilization
    of two programming abstractions: one to separate the symbolic fixpoint computations
    from the predecessor calculations, and another one to allow the integration of
    different BDD libraries as back-ends. In particular, we employ a multi-threaded
    execution of the fixpoint algorithm by using the multi-threaded BDD library Sylvan,
    which leads to enormous computational savings.'
acknowledgement: 'Authors ordered alphabetically. R. Majumdar and A.-K. Schmuck are
  partially supported by DFG project 389792660 TRR 248-CPEC. A.-K. Schmuck is additionally
  funded through DFG project (SCHM 3541/1-1). K. Mallik is supported by the ERC project
  ERC-2020-AdG 101020093. M. Rychlicki is supported by the EPSRC project EP/V00252X/1.
  S. Soudjani is supported by the following projects: EPSRC EP/V043676/1, EIC 101070802,
  and ERC 101089047.'
alternative_title:
- LNCS
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Rupak
  full_name: Majumdar, Rupak
  last_name: Majumdar
- first_name: Kaushik
  full_name: Mallik, Kaushik
  id: 0834ff3c-6d72-11ec-94e0-b5b0a4fb8598
  last_name: Mallik
  orcid: 0000-0001-9864-7475
- first_name: Mateusz
  full_name: Rychlicki, Mateusz
  last_name: Rychlicki
- first_name: Anne-Kathrin
  full_name: Schmuck, Anne-Kathrin
  last_name: Schmuck
- first_name: Sadegh
  full_name: Soudjani, Sadegh
  last_name: Soudjani
citation:
  ama: 'Majumdar R, Mallik K, Rychlicki M, Schmuck A-K, Soudjani S. A flexible toolchain
    for symbolic rabin games under fair and stochastic uncertainties. In: <i>35th
    International Conference on Computer Aided Verification</i>. Vol 13966. Springer
    Nature; 2023:3-15. doi:<a href="https://doi.org/10.1007/978-3-031-37709-9_1">10.1007/978-3-031-37709-9_1</a>'
  apa: 'Majumdar, R., Mallik, K., Rychlicki, M., Schmuck, A.-K., &#38; Soudjani, S.
    (2023). A flexible toolchain for symbolic rabin games under fair and stochastic
    uncertainties. In <i>35th International Conference on Computer Aided Verification</i>
    (Vol. 13966, pp. 3–15). Paris, France: Springer Nature. <a href="https://doi.org/10.1007/978-3-031-37709-9_1">https://doi.org/10.1007/978-3-031-37709-9_1</a>'
  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 <i>35th International Conference on Computer
    Aided Verification</i>, 13966:3–15. Springer Nature, 2023. <a href="https://doi.org/10.1007/978-3-031-37709-9_1">https://doi.org/10.1007/978-3-031-37709-9_1</a>.
  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
    <i>35th International Conference on Computer Aided Verification</i>, 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.” <i>35th International Conference on Computer
    Aided Verification</i>, vol. 13966, Springer Nature, 2023, pp. 3–15, doi:<a href="https://doi.org/10.1007/978-3-031-37709-9_1">10.1007/978-3-031-37709-9_1</a>.
  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
corr_author: '1'
date_created: 2024-01-08T13:18:00Z
date_published: 2023-07-16T00:00:00Z
date_updated: 2025-09-09T14:16:49Z
day: '16'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1007/978-3-031-37709-9_1
ec_funded: 1
external_id:
  isi:
  - '001310805600001'
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
  file_id: '14765'
  file_name: 2023_LNCSCAV_Majumdar.pdf
  file_size: 405147
  relation: main_file
  success: 1
file_date_updated: 2024-01-09T10:01:07Z
has_accepted_license: '1'
intvolume: '     13966'
isi: 1
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 3-15
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
publication: 35th International Conference on Computer Aided Verification
publication_identifier:
  eisbn:
  - '9783031377099'
  eissn:
  - 1611-3349
  isbn:
  - '9783031377082'
  issn:
  - 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
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scopus_import: '1'
status: public
title: A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties
tmp:
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  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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 13966
year: '2023'
...
---
OA_place: repository
OA_type: green
_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
arxiv: 1
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: <i>Proceedings of the
    37th AAAI Conference on Artificial Intelligence</i>. Vol 37. Association for the
    Advancement of Artificial Intelligence; 2023:11926-11935. doi:<a href="https://doi.org/10.1609/aaai.v37i10.26407">10.1609/aaai.v37i10.26407</a>'
  apa: 'Zikelic, D., Lechner, M., Henzinger, T. A., &#38; Chatterjee, K. (2023). Learning
    control policies for stochastic systems with reach-avoid guarantees. In <i>Proceedings
    of the 37th AAAI Conference on Artificial Intelligence</i> (Vol. 37, pp. 11926–11935).
    Washington, DC, United States: Association for the Advancement of Artificial Intelligence.
    <a href="https://doi.org/10.1609/aaai.v37i10.26407">https://doi.org/10.1609/aaai.v37i10.26407</a>'
  chicago: Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee.
    “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.”
    In <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>,
    37:11926–35. Association for the Advancement of Artificial Intelligence, 2023.
    <a href="https://doi.org/10.1609/aaai.v37i10.26407">https://doi.org/10.1609/aaai.v37i10.26407</a>.
  ieee: D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control
    policies for stochastic systems with reach-avoid guarantees,” in <i>Proceedings
    of the 37th AAAI Conference on Artificial Intelligence</i>, 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.” <i>Proceedings of the 37th AAAI Conference on Artificial
    Intelligence</i>, vol. 37, no. 10, Association for the Advancement of Artificial
    Intelligence, 2023, pp. 11926–35, doi:<a href="https://doi.org/10.1609/aaai.v37i10.26407">10.1609/aaai.v37i10.26407</a>.
  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
corr_author: '1'
date_created: 2024-01-18T07:44:31Z
date_published: 2023-06-26T00:00:00Z
date_updated: 2025-07-03T11:38:12Z
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
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/2210.05308
month: '06'
oa: 1
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'
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    status: public
scopus_import: '1'
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: '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
arxiv: 1
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. <i>TheoretiCS</i>. 2023;2.
    doi:<a href="https://doi.org/10.46298/theoretics.23.4">10.46298/theoretics.23.4</a>
  apa: Banerjee, T., Majumdar, R., Mallik, K., Schmuck, A.-K., &#38; Soudjani, S.
    (2023). Fast symbolic algorithms for mega-regular games under strong transition
    fairness. <i>TheoretiCS</i>. EPI Sciences. <a href="https://doi.org/10.46298/theoretics.23.4">https://doi.org/10.46298/theoretics.23.4</a>
  chicago: Banerjee, Tamajit, Rupak Majumdar, Kaushik Mallik, Anne-Kathrin Schmuck,
    and Sadegh Soudjani. “Fast Symbolic Algorithms for Mega-Regular Games under Strong
    Transition Fairness.” <i>TheoretiCS</i>. EPI Sciences, 2023. <a href="https://doi.org/10.46298/theoretics.23.4">https://doi.org/10.46298/theoretics.23.4</a>.
  ieee: T. Banerjee, R. Majumdar, K. Mallik, A.-K. Schmuck, and S. Soudjani, “Fast
    symbolic algorithms for mega-regular games under strong transition fairness,”
    <i>TheoretiCS</i>, 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.” <i>TheoretiCS</i>, vol. 2, 4, EPI Sciences,
    2023, doi:<a href="https://doi.org/10.46298/theoretics.23.4">10.46298/theoretics.23.4</a>.
  short: T. Banerjee, R. Majumdar, K. Mallik, A.-K. Schmuck, S. Soudjani, TheoretiCS
    2 (2023).
corr_author: '1'
date_created: 2024-01-31T13:40:49Z
date_published: 2023-02-24T00:00:00Z
date_updated: 2025-04-14T07:55:57Z
day: '24'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.46298/theoretics.23.4
ec_funded: 1
external_id:
  arxiv:
  - '2202.07480'
file:
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  creator: dernst
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  date_updated: 2024-02-05T10:19:35Z
  file_id: '14940'
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  file_size: 917076
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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: '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:<a
    href="https://doi.org/10.5281/ZENODO.7877790">10.5281/ZENODO.7877790</a>
  apa: Majumdar, R., Mallik, K., Rychlicki, M., Schmuck, A.-K., &#38; Soudjani, S.
    (2023). A flexible toolchain for symbolic rabin games under fair and stochastic
    uncertainties. Zenodo. <a href="https://doi.org/10.5281/ZENODO.7877790">https://doi.org/10.5281/ZENODO.7877790</a>
  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. <a href="https://doi.org/10.5281/ZENODO.7877790">https://doi.org/10.5281/ZENODO.7877790</a>.
  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,
    <a href="https://doi.org/10.5281/ZENODO.7877790">10.5281/ZENODO.7877790</a>.
  mla: Majumdar, Rupak, et al. <i>A Flexible Toolchain for Symbolic Rabin Games under
    Fair and Stochastic Uncertainties</i>. Zenodo, 2023, doi:<a href="https://doi.org/10.5281/ZENODO.7877790">10.5281/ZENODO.7877790</a>.
  short: R. Majumdar, K. Mallik, M. Rychlicki, A.-K. Schmuck, S. Soudjani, (2023).
corr_author: '1'
date_created: 2024-02-14T15:13:00Z
date_published: 2023-04-28T00:00:00Z
date_updated: 2025-09-09T14:16:48Z
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
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status: public
title: A flexible toolchain for symbolic rabin games under fair and stochastic uncertainties
tmp:
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  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
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type: research_data_reference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
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:<a href="https://doi.org/10.5281/ZENODO.8191723">10.5281/ZENODO.8191723</a>
  apa: Chalupa, M., &#38; Henzinger, T. A. (2023). Monitoring hyperproperties with
    prefix transducers. Zenodo. <a href="https://doi.org/10.5281/ZENODO.8191723">https://doi.org/10.5281/ZENODO.8191723</a>
  chicago: Chalupa, Marek, and Thomas A Henzinger. “Monitoring Hyperproperties with
    Prefix Transducers.” Zenodo, 2023. <a href="https://doi.org/10.5281/ZENODO.8191723">https://doi.org/10.5281/ZENODO.8191723</a>.
  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, <a href="https://doi.org/10.5281/ZENODO.8191723">10.5281/ZENODO.8191723</a>.
  mla: Chalupa, Marek, and Thomas A. Henzinger. <i>Monitoring Hyperproperties with
    Prefix Transducers</i>. Zenodo, 2023, doi:<a href="https://doi.org/10.5281/ZENODO.8191723">10.5281/ZENODO.8191723</a>.
  short: M. Chalupa, T.A. Henzinger, (2023).
corr_author: '1'
date_created: 2024-02-28T07:34:34Z
date_published: 2023-07-28T00:00:00Z
date_updated: 2025-04-14T09:42:55Z
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: '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: <i>Proceedings
    of the 23rd Conference on Formal Methods in Computer-Aided Design</i>. TU Wien
    Academic Press; 2023:122-131. doi:<a href="https://doi.org/10.34727/2023/isbn.978-3-85448-060-0_20">10.34727/2023/isbn.978-3-85448-060-0_20</a>'
  apa: 'Pastva, S., &#38; Henzinger, T. A. (2023). Binary decision diagrams on modern
    hardware. In <i>Proceedings of the 23rd Conference on Formal Methods in Computer-Aided
    Design</i> (pp. 122–131). Ames, IA, United States: TU Wien Academic Press. <a
    href="https://doi.org/10.34727/2023/isbn.978-3-85448-060-0_20">https://doi.org/10.34727/2023/isbn.978-3-85448-060-0_20</a>'
  chicago: Pastva, Samuel, and Thomas A Henzinger. “Binary Decision Diagrams on Modern
    Hardware.” In <i>Proceedings of the 23rd Conference on Formal Methods in Computer-Aided
    Design</i>, 122–31. TU Wien Academic Press, 2023. <a href="https://doi.org/10.34727/2023/isbn.978-3-85448-060-0_20">https://doi.org/10.34727/2023/isbn.978-3-85448-060-0_20</a>.
  ieee: S. Pastva and T. A. Henzinger, “Binary decision diagrams on modern hardware,”
    in <i>Proceedings of the 23rd Conference on Formal Methods in Computer-Aided Design</i>,
    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: Formal Methods in Computer-Aided Design, 122–131.'
  mla: Pastva, Samuel, and Thomas A. Henzinger. “Binary Decision Diagrams on Modern
    Hardware.” <i>Proceedings of the 23rd Conference on Formal Methods in Computer-Aided
    Design</i>, TU Wien Academic Press, 2023, pp. 122–31, doi:<a href="https://doi.org/10.34727/2023/isbn.978-3-85448-060-0_20">10.34727/2023/isbn.978-3-85448-060-0_20</a>.
  short: S. Pastva, T.A. Henzinger, in:, Proceedings of the 23rd Conference on Formal
    Methods in Computer-Aided Design, TU Wien Academic Press, 2023, pp. 122–131.
conference:
  end_date: 2023-10-27
  location: Ames, IA, United States
  name: 'FMCAD: Formal Methods in Computer-Aided Design'
  start_date: 2023-10-25
corr_author: '1'
das_tickbox: '1'
date_created: 2023-12-31T23:01:03Z
date_published: 2023-10-01T00:00:00Z
date_updated: 2026-07-07T05:58:51Z
day: '01'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.34727/2023/isbn.978-3-85448-060-0_20
ec_funded: 1
external_id:
  isi:
  - '001504402400020'
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'
isi: 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 Wien 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: '14243'
abstract:
- lang: eng
  text: 'Two-player zero-sum "graph games" are central in logic, verification, and
    multi-agent systems. The game proceeds by placing a token on a vertex of a graph,
    and allowing the players to move it to produce an infinite path, which determines
    the winner or payoff of the game. Traditionally, the players alternate turns in
    moving the token. In "bidding games", however, the players have budgets and in
    each turn, an auction (bidding) determines which player moves the token. So far,
    bidding games have only been studied as full-information games. In this work we
    initiate the study of partial-information bidding games: we study bidding games
    in which a player''s initial budget is drawn from a known probability distribution.
    We show that while for some bidding mechanisms and objectives, it is straightforward
    to adapt the results from the full-information setting to the partial-information
    setting, for others, the analysis is significantly more challenging, requires
    new techniques, and gives rise to interesting results. Specifically, we study
    games with "mean-payoff" objectives in combination with "poorman" bidding. We
    construct optimal strategies for a partially-informed player who plays against
    a fully-informed adversary. We show that, somewhat surprisingly, the "value" under
    pure strategies does not necessarily exist in such games.'
acknowledgement: This research was supported in part by ISF grant no.1679/21, by the
  ERC CoG 863818 (ForM-SMArt), and the European Union’s Horizon 2020 research and
  innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
article_processing_charge: No
arxiv: 1
author:
- first_name: Guy
  full_name: Avni, Guy
  id: 463C8BC2-F248-11E8-B48F-1D18A9856A87
  last_name: Avni
  orcid: 0000-0001-5588-8287
- first_name: Ismael R
  full_name: Jecker, Ismael R
  id: 85D7C63E-7D5D-11E9-9C0F-98C4E5697425
  last_name: Jecker
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
citation:
  ama: 'Avni G, Jecker IR, Zikelic D. Bidding graph games with partially-observable
    budgets. In: <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>.
    Vol 37. AAAI Press; 2023:5464-5471. doi:<a href="https://doi.org/10.1609/aaai.v37i5.25679">10.1609/aaai.v37i5.25679</a>'
  apa: 'Avni, G., Jecker, I. R., &#38; Zikelic, D. (2023). Bidding graph games with
    partially-observable budgets. In <i>Proceedings of the 37th AAAI Conference on
    Artificial Intelligence</i> (Vol. 37, pp. 5464–5471). Washington, DC, United States:
    AAAI Press. <a href="https://doi.org/10.1609/aaai.v37i5.25679">https://doi.org/10.1609/aaai.v37i5.25679</a>'
  chicago: Avni, Guy, Ismael R Jecker, and Dorde Zikelic. “Bidding Graph Games with
    Partially-Observable Budgets.” In <i>Proceedings of the 37th AAAI Conference on
    Artificial Intelligence</i>, 37:5464–71. AAAI Press, 2023. <a href="https://doi.org/10.1609/aaai.v37i5.25679">https://doi.org/10.1609/aaai.v37i5.25679</a>.
  ieee: G. Avni, I. R. Jecker, and D. Zikelic, “Bidding graph games with partially-observable
    budgets,” in <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>,
    Washington, DC, United States, 2023, vol. 37, no. 5, pp. 5464–5471.
  ista: 'Avni G, Jecker IR, Zikelic D. 2023. Bidding graph games with partially-observable
    budgets. Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI:
    Conference on Artificial Intelligence vol. 37, 5464–5471.'
  mla: Avni, Guy, et al. “Bidding Graph Games with Partially-Observable Budgets.”
    <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, vol.
    37, no. 5, AAAI Press, 2023, pp. 5464–71, doi:<a href="https://doi.org/10.1609/aaai.v37i5.25679">10.1609/aaai.v37i5.25679</a>.
  short: G. Avni, I.R. Jecker, D. Zikelic, in:, Proceedings of the 37th AAAI Conference
    on Artificial Intelligence, AAAI Press, 2023, pp. 5464–5471.
conference:
  end_date: 2023-02-14
  location: Washington, DC, United States
  name: 'AAAI: Conference on Artificial Intelligence'
  start_date: 2023-02-07
das_tickbox: '1'
date_created: 2023-08-27T22:01:18Z
date_published: 2023-06-27T00:00:00Z
date_updated: 2026-07-07T06:24:15Z
day: '27'
ddc:
- '000'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v37i5.25679
ec_funded: 1
external_id:
  arxiv:
  - '2211.13626'
intvolume: '        37'
issue: '5'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.1609/aaai.v37i5.25679
month: '06'
oa: 1
oa_version: Published Version
page: 5464-5471
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication: Proceedings of the 37th AAAI Conference on Artificial Intelligence
publication_identifier:
  isbn:
  - '9781577358800'
publication_status: published
publisher: AAAI Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Bidding graph games with partially-observable budgets
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2023'
...
---
_id: '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)."
alternative_title:
- Advances in Neural Information Processing Systems
article_processing_charge: No
arxiv: 1
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: <i>37th Conference
    on Neural Information Processing Systems</i>. Neural Information Processing Systems
    Foundation; 2023.'
  apa: 'Zikelic, D., Lechner, M., Verma, A., Chatterjee, K., &#38; Henzinger, T. A.
    (2023). Compositional policy learning in stochastic control systems with formal
    guarantees. In <i>37th Conference on Neural Information Processing Systems</i>.
    New Orleans, LO, United States: Neural Information Processing Systems Foundation.'
  chicago: Zikelic, Dorde, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee,
    and Thomas A Henzinger. “Compositional Policy Learning in Stochastic Control Systems
    with Formal Guarantees.” In <i>37th Conference on Neural Information Processing
    Systems</i>. Neural Information Processing Systems Foundation, 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 <i>37th
    Conference on Neural Information Processing Systems</i>, 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, Advances in Neural Information Processing Systems, .'
  mla: Zikelic, Dorde, et al. “Compositional Policy Learning in Stochastic Control
    Systems with Formal Guarantees.” <i>37th Conference on Neural Information Processing
    Systems</i>, Neural Information Processing Systems Foundation, 2023.
  short: D. Zikelic, M. Lechner, A. Verma, K. Chatterjee, T.A. Henzinger, in:, 37th
    Conference on Neural Information Processing Systems, Neural Information Processing
    Systems Foundation, 2023.
conference:
  end_date: 2023-12-16
  location: New Orleans, LO, United States
  name: 'NeurIPS: Neural Information Processing Systems'
  start_date: 2023-12-10
corr_author: '1'
das_tickbox: '1'
date_created: 2024-02-25T09:23:24Z
date_published: 2023-12-15T00:00:00Z
date_updated: 2026-07-07T06:36:54Z
day: '15'
ddc:
- '000'
department:
- _id: ToHe
- _id: KrCh
ec_funded: 1
external_id:
  arxiv:
  - '2312.01456'
file:
- access_level: open_access
  checksum: 739c6d72506b778302d4e708723bf12c
  content_type: application/pdf
  creator: dernst
  date_created: 2024-07-22T11:45:17Z
  date_updated: 2024-07-22T11:45:17Z
  file_id: '17309'
  file_name: 2023_NeurIPS_Zikelic.pdf
  file_size: 562008
  relation: main_file
  success: 1
file_date_updated: 2024-07-22T11:45:17Z
has_accepted_license: '1'
language:
- iso: eng
month: '12'
oa: 1
oa_version: Published Version
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_identifier:
  eissn:
  - 1049-5258
publication_status: published
publisher: Neural Information Processing Systems Foundation
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: '13221'
abstract:
- lang: eng
  text: The safety-liveness dichotomy is a fundamental concept in formal languages
    which plays a key role in verification. Recently, this dichotomy has been lifted
    to quantitative properties, which are arbitrary functions from infinite words
    to partially-ordered domains. We look into harnessing the dichotomy for the specific
    classes of quantitative properties expressed by quantitative automata. These automata
    contain finitely many states and rational-valued transition weights, and their
    common value functions Inf, Sup, LimInf, LimSup, LimInfAvg, LimSupAvg, and DSum
    map infinite words into the totallyordered domain of real numbers. In this automata-theoretic
    setting, we establish a connection between quantitative safety and topological
    continuity and provide an alternative characterization of quantitative safety
    and liveness in terms of their boolean counterparts. For all common value functions,
    we show how the safety closure of a quantitative automaton can be constructed
    in PTime, and we provide PSpace-complete checks of whether a given quantitative
    automaton is safe or live, with the exception of LimInfAvg and LimSupAvg automata,
    for which the safety check is in ExpSpace. Moreover, for deterministic Sup, LimInf,
    and LimSup automata, we give PTime decompositions into safe and live automata.
    These decompositions enable the separation of techniques for safety and liveness
    verification for quantitative specifications.
acknowledgement: We thank Christof Löding for pointing us to some results on PSpace-hardess
  of universality problems and the anonymous reviewers for their helpful comments.
  This work was supported in part by the ERC-2020-AdG 101020093 and the Israel Science
  Foundation grant 2410/22.
alternative_title:
- LIPIcs
article_number: '17'
article_processing_charge: No
arxiv: 1
author:
- first_name: Udi
  full_name: Boker, Udi
  id: 31E297B6-F248-11E8-B48F-1D18A9856A87
  last_name: Boker
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
- first_name: Nicolas Adrien
  full_name: Mazzocchi, Nicolas Adrien
  id: b26baa86-3308-11ec-87b0-8990f34baa85
  last_name: Mazzocchi
- first_name: Naci E
  full_name: Sarac, Naci E
  id: 8C6B42F8-C8E6-11E9-A03A-F2DCE5697425
  last_name: Sarac
citation:
  ama: 'Boker U, Henzinger TA, Mazzocchi NA, Sarac NE. Safety and liveness of quantitative
    automata. In: <i>34th International Conference on Concurrency Theory</i>. Vol
    279. Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2023. doi:<a href="https://doi.org/10.4230/LIPIcs.CONCUR.2023.17">10.4230/LIPIcs.CONCUR.2023.17</a>'
  apa: 'Boker, U., Henzinger, T. A., Mazzocchi, N. A., &#38; Sarac, N. E. (2023).
    Safety and liveness of quantitative automata. In <i>34th International Conference
    on Concurrency Theory</i> (Vol. 279). Antwerp, Belgium: Schloss Dagstuhl - Leibniz-Zentrum
    für Informatik. <a href="https://doi.org/10.4230/LIPIcs.CONCUR.2023.17">https://doi.org/10.4230/LIPIcs.CONCUR.2023.17</a>'
  chicago: Boker, Udi, Thomas A Henzinger, Nicolas Adrien Mazzocchi, and Naci E Sarac.
    “Safety and Liveness of Quantitative Automata.” In <i>34th International Conference
    on Concurrency Theory</i>, Vol. 279. Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
    2023. <a href="https://doi.org/10.4230/LIPIcs.CONCUR.2023.17">https://doi.org/10.4230/LIPIcs.CONCUR.2023.17</a>.
  ieee: U. Boker, T. A. Henzinger, N. A. Mazzocchi, and N. E. Sarac, “Safety and liveness
    of quantitative automata,” in <i>34th International Conference on Concurrency
    Theory</i>, Antwerp, Belgium, 2023, vol. 279.
  ista: 'Boker U, Henzinger TA, Mazzocchi NA, Sarac NE. 2023. Safety and liveness
    of quantitative automata. 34th International Conference on Concurrency Theory.
    CONCUR: Conference on Concurrency Theory, LIPIcs, vol. 279, 17.'
  mla: Boker, Udi, et al. “Safety and Liveness of Quantitative Automata.” <i>34th
    International Conference on Concurrency Theory</i>, vol. 279, 17, Schloss Dagstuhl
    - Leibniz-Zentrum für Informatik, 2023, doi:<a href="https://doi.org/10.4230/LIPIcs.CONCUR.2023.17">10.4230/LIPIcs.CONCUR.2023.17</a>.
  short: U. Boker, T.A. Henzinger, N.A. Mazzocchi, N.E. Sarac, in:, 34th International
    Conference on Concurrency Theory, Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
    2023.
conference:
  end_date: 2023-09-23
  location: Antwerp, Belgium
  name: 'CONCUR: Conference on Concurrency Theory'
  start_date: 2023-09-18
corr_author: '1'
date_created: 2023-07-14T10:00:15Z
date_published: 2023-09-01T00:00:00Z
date_updated: 2026-07-27T12:48:18Z
day: '01'
ddc:
- '000'
department:
- _id: GradSch
- _id: ToHe
doi: 10.4230/LIPIcs.CONCUR.2023.17
ec_funded: 1
external_id:
  arxiv:
  - '2307.06016'
  isi:
  - '001570542500017'
file:
- access_level: open_access
  checksum: d40e57a04448ea5c77d7e1cfb9590a81
  content_type: application/pdf
  creator: esarac
  date_created: 2023-07-14T12:03:48Z
  date_updated: 2023-07-14T12:03:48Z
  file_id: '13224'
  file_name: CONCUR23.pdf
  file_size: 755529
  relation: main_file
  success: 1
file_date_updated: 2023-07-14T12:03:48Z
has_accepted_license: '1'
intvolume: '       279'
isi: 1
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
publication: 34th International Conference on Concurrency Theory
publication_identifier:
  eissn:
  - 1868-8969
  isbn:
  - '9783959772990'
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
related_material:
  record:
  - id: '20342'
    relation: later_version
    status: public
  - id: '20147'
    relation: dissertation_contains
    status: public
scopus_import: '1'
status: public
title: Safety and liveness of quantitative automata
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 279
year: '2023'
...
---
_id: '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: <i>Software Verification</i>.
    Vol 13124. LNCS. Springer Nature; 2022:3-6. doi:<a href="https://doi.org/10.1007/978-3-030-95561-8_1">10.1007/978-3-030-95561-8_1</a>'
  apa: 'Henzinger, T. A. (2022). Quantitative monitoring of software. In <i>Software
    Verification</i> (Vol. 13124, pp. 3–6). New Haven, CT, United States: Springer
    Nature. <a href="https://doi.org/10.1007/978-3-030-95561-8_1">https://doi.org/10.1007/978-3-030-95561-8_1</a>'
  chicago: Henzinger, Thomas A. “Quantitative Monitoring of Software.” In <i>Software
    Verification</i>, 13124:3–6. LNCS. Springer Nature, 2022. <a href="https://doi.org/10.1007/978-3-030-95561-8_1">https://doi.org/10.1007/978-3-030-95561-8_1</a>.
  ieee: T. A. Henzinger, “Quantitative monitoring of software,” in <i>Software Verification</i>,
    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.” <i>Software Verification</i>,
    vol. 13124, Springer Nature, 2022, pp. 3–6, doi:<a href="https://doi.org/10.1007/978-3-030-95561-8_1">10.1007/978-3-030-95561-8_1</a>.
  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
corr_author: '1'
date_created: 2022-03-20T23:01:40Z
date_published: 2022-02-22T00:00:00Z
date_updated: 2025-04-15T06:25:58Z
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: Formal methods for the design and analysis of complex systems
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: <i>Fundamental Approaches to Software Engineering</i>. Vol 13241.
    Springer Nature; 2022:3-22. doi:<a href="https://doi.org/10.1007/978-3-030-99429-7_1">10.1007/978-3-030-99429-7_1</a>'
  apa: 'Bartocci, E., Ferrere, T., Henzinger, T. A., Nickovic, D., &#38; Da Costa,
    A. O. (2022). Information-flow interfaces. In <i>Fundamental Approaches to Software
    Engineering</i> (Vol. 13241, pp. 3–22). Munich, Germany: Springer Nature. <a href="https://doi.org/10.1007/978-3-030-99429-7_1">https://doi.org/10.1007/978-3-030-99429-7_1</a>'
  chicago: Bartocci, Ezio, Thomas Ferrere, Thomas A Henzinger, Dejan Nickovic, and
    Ana Oliveira Da Costa. “Information-Flow Interfaces.” In <i>Fundamental Approaches
    to Software Engineering</i>, 13241:3–22. Springer Nature, 2022. <a href="https://doi.org/10.1007/978-3-030-99429-7_1">https://doi.org/10.1007/978-3-030-99429-7_1</a>.
  ieee: E. Bartocci, T. Ferrere, T. A. Henzinger, D. Nickovic, and A. O. Da Costa,
    “Information-flow interfaces,” in <i>Fundamental Approaches to Software Engineering</i>,
    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.” <i>Fundamental Approaches
    to Software Engineering</i>, vol. 13241, Springer Nature, 2022, pp. 3–22, doi:<a
    href="https://doi.org/10.1007/978-3-030-99429-7_1">10.1007/978-3-030-99429-7_1</a>.
  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: 2025-12-30T06:50:51Z
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'
related_material:
  record:
  - id: '17094'
    relation: extended_version
    status: public
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'
...
---
OA_place: repository
_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
arxiv: 1
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. <i>arXiv</i>. doi:<a href="https://doi.org/10.48550/arXiv.2204.07373">10.48550/arXiv.2204.07373</a>
  apa: Lechner, M., Amini, A., Rus, D., &#38; Henzinger, T. A. (n.d.). Revisiting
    the adversarial robustness-accuracy tradeoff in robot learning. <i>arXiv</i>.
    <a href="https://doi.org/10.48550/arXiv.2204.07373">https://doi.org/10.48550/arXiv.2204.07373</a>
  chicago: Lechner, Mathias, Alexander Amini, Daniela Rus, and Thomas A Henzinger.
    “Revisiting the Adversarial Robustness-Accuracy Tradeoff in Robot Learning.” <i>ArXiv</i>,
    n.d. <a href="https://doi.org/10.48550/arXiv.2204.07373">https://doi.org/10.48550/arXiv.2204.07373</a>.
  ieee: M. Lechner, A. Amini, D. Rus, and T. A. Henzinger, “Revisiting the adversarial
    robustness-accuracy tradeoff in robot learning,” <i>arXiv</i>. .
  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.” <i>ArXiv</i>, 2204.07373, doi:<a href="https://doi.org/10.48550/arXiv.2204.07373">10.48550/arXiv.2204.07373</a>.
  short: M. Lechner, A. Amini, D. Rus, T.A. Henzinger, ArXiv (n.d.).
corr_author: '1'
date_created: 2022-05-12T13:20:17Z
date_published: 2022-04-15T00:00:00Z
date_updated: 2026-04-07T14:21:58Z
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: draft
related_material:
  record:
  - id: '12704'
    relation: later_version
    status: public
  - id: '11362'
    relation: dissertation_contains
    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: '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
arxiv: 1
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: <i>2022 International Conference
    on Robotics and Automation</i>. IEEE; 2022:7513-7520. doi:<a href="https://doi.org/10.1109/ICRA46639.2022.9811650">10.1109/ICRA46639.2022.9811650</a>'
  apa: 'Brunnbauer, A., Berducci, L., Brandstatter, A., Lechner, M., Hasani, R., Rus,
    D., &#38; Grosu, R. (2022). Latent imagination facilitates zero-shot transfer
    in autonomous racing. In <i>2022 International Conference on Robotics and Automation</i>
    (pp. 7513–7520). Philadelphia, PA, United States: IEEE. <a href="https://doi.org/10.1109/ICRA46639.2022.9811650">https://doi.org/10.1109/ICRA46639.2022.9811650</a>'
  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 <i>2022 International Conference on Robotics
    and Automation</i>, 7513–20. IEEE, 2022. <a href="https://doi.org/10.1109/ICRA46639.2022.9811650">https://doi.org/10.1109/ICRA46639.2022.9811650</a>.
  ieee: A. Brunnbauer <i>et al.</i>, “Latent imagination facilitates zero-shot transfer
    in autonomous racing,” in <i>2022 International Conference on Robotics and Automation</i>,
    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.” <i>2022 International Conference on Robotics and Automation</i>,
    IEEE, 2022, pp. 7513–20, doi:<a href="https://doi.org/10.1109/ICRA46639.2022.9811650">10.1109/ICRA46639.2022.9811650</a>.
  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: 2025-09-10T09:39:53Z
day: '12'
department:
- _id: ToHe
doi: 10.1109/ICRA46639.2022.9811650
ec_funded: 1
external_id:
  arxiv:
  - '2103.04909'
  isi:
  - '000941277600124'
isi: 1
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: Formal methods for the design and analysis of complex systems
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
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
arxiv: 1
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.
    <i>Nature Machine Intelligence</i>. 2022;4(11):992-1003. doi:<a href="https://doi.org/10.1038/s42256-022-00556-7">10.1038/s42256-022-00556-7</a>
  apa: Hasani, R., Lechner, M., Amini, A., Liebenwein, L., Ray, A., Tschaikowski,
    M., … Rus, D. (2022). Closed-form continuous-time neural networks. <i>Nature Machine
    Intelligence</i>. Springer Nature. <a href="https://doi.org/10.1038/s42256-022-00556-7">https://doi.org/10.1038/s42256-022-00556-7</a>
  chicago: Hasani, Ramin, Mathias Lechner, Alexander Amini, Lucas Liebenwein, Aaron
    Ray, Max Tschaikowski, Gerald Teschl, and Daniela Rus. “Closed-Form Continuous-Time
    Neural Networks.” <i>Nature Machine Intelligence</i>. Springer Nature, 2022. <a
    href="https://doi.org/10.1038/s42256-022-00556-7">https://doi.org/10.1038/s42256-022-00556-7</a>.
  ieee: R. Hasani <i>et al.</i>, “Closed-form continuous-time neural networks,” <i>Nature
    Machine Intelligence</i>, 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.” <i>Nature
    Machine Intelligence</i>, vol. 4, no. 11, Springer Nature, 2022, pp. 992–1003,
    doi:<a href="https://doi.org/10.1038/s42256-022-00556-7">10.1038/s42256-022-00556-7</a>.
  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: 2025-04-15T06:26:02Z
day: '15'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1038/s42256-022-00556-7
external_id:
  arxiv:
  - '2106.13898'
  isi:
  - '000884215600003'
file:
- access_level: open_access
  checksum: b4789122ce04bfb4ac042390f59aaa8b
  content_type: application/pdf
  creator: dernst
  date_created: 2023-01-24T09:49:44Z
  date_updated: 2023-01-24T09:49:44Z
  file_id: '12355'
  file_name: 2022_NatureMachineIntelligence_Hasani.pdf
  file_size: 3259553
  relation: main_file
  success: 1
file_date_updated: 2023-01-24T09:49:44Z
has_accepted_license: '1'
intvolume: '         4'
isi: 1
issue: '11'
keyword:
- Artificial Intelligence
- Computer Networks and Communications
- Computer Vision and Pattern Recognition
- Human-Computer Interaction
- Software
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: 992-1003
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: Z211
  name: Formal methods for the design and analysis of complex systems
publication: Nature Machine Intelligence
publication_identifier:
  issn:
  - 2522-5839
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
  link:
  - relation: erratum
    url: https://doi.org/10.1038/s42256-022-00597-y
scopus_import: '1'
status: public
title: Closed-form continuous-time neural networks
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 4
year: '2022'
...
---
_id: '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
arxiv: 1
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: <i>20th International Symposium on Automated Technology
    for Verification and Analysis</i>. Vol 13505. Springer Nature; 2022:337-353. doi:<a
    href="https://doi.org/10.1007/978-3-031-19992-9_22">10.1007/978-3-031-19992-9_22</a>'
  apa: 'Garcia Soto, M., Henzinger, T. A., &#38; Schilling, C. (2022). Synthesis of parametric
    hybrid automata from time series. In <i>20th International Symposium on Automated
    Technology for Verification and Analysis</i> (Vol. 13505, pp. 337–353). Virtual:
    Springer Nature. <a href="https://doi.org/10.1007/978-3-031-19992-9_22">https://doi.org/10.1007/978-3-031-19992-9_22</a>'
  chicago: Garcia Soto, Miriam, Thomas A Henzinger, and Christian Schilling. “Synthesis
    of Parametric Hybrid Automata from Time Series.” In <i>20th International Symposium
    on Automated Technology for Verification and Analysis</i>, 13505:337–53. Springer
    Nature, 2022. <a href="https://doi.org/10.1007/978-3-031-19992-9_22">https://doi.org/10.1007/978-3-031-19992-9_22</a>.
  ieee: M. Garcia Soto, T. A. Henzinger, and C. Schilling, “Synthesis of parametric
    hybrid automata from time series,” in <i>20th International Symposium on Automated
    Technology for Verification and Analysis</i>, 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.” <i>20th International Symposium on Automated Technology for Verification
    and Analysis</i>, vol. 13505, Springer Nature, 2022, pp. 337–53, doi:<a href="https://doi.org/10.1007/978-3-031-19992-9_22">10.1007/978-3-031-19992-9_22</a>.
  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
corr_author: '1'
date_created: 2023-01-12T12:11:16Z
date_published: 2022-10-21T00:00:00Z
date_updated: 2025-09-10T09:50:08Z
day: '21'
department:
- _id: ToHe
doi: 10.1007/978-3-031-19992-9_22
ec_funded: 1
external_id:
  arxiv:
  - '2208.06383'
  isi:
  - '001456146500022'
intvolume: '     13505'
isi: 1
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: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 13505
year: '2022'
...
---
_id: '12175'
abstract:
- lang: eng
  text: An automaton is history-deterministic (HD) if one can safely resolve its non-deterministic
    choices on the fly. In a recent paper, Henzinger, Lehtinen and Totzke studied
    this in the context of Timed Automata [9], where it was conjectured that the class
    of timed ω-languages recognised by HD-timed automata strictly extends that of
    deterministic ones. We provide a proof for this fact.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, the
  EPSRC project EP/V025848/1, and the EPSRC project EP/X017796/1.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Sougata
  full_name: Bose, Sougata
  last_name: Bose
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
- first_name: Karoliina
  full_name: Lehtinen, Karoliina
  last_name: Lehtinen
- first_name: Sven
  full_name: Schewe, Sven
  last_name: Schewe
- first_name: Patrick
  full_name: Totzke, Patrick
  last_name: Totzke
citation:
  ama: 'Bose S, Henzinger TA, Lehtinen K, Schewe S, Totzke P. History-deterministic
    timed automata are not determinizable. In: <i>16th International Conference on
    Reachability Problems</i>. Vol 13608. Springer Nature; 2022:67-76. doi:<a href="https://doi.org/10.1007/978-3-031-19135-0_5">10.1007/978-3-031-19135-0_5</a>'
  apa: 'Bose, S., Henzinger, T. A., Lehtinen, K., Schewe, S., &#38; Totzke, P. (2022).
    History-deterministic timed automata are not determinizable. In <i>16th International
    Conference on Reachability Problems</i> (Vol. 13608, pp. 67–76). Kaiserslautern,
    Germany: Springer Nature. <a href="https://doi.org/10.1007/978-3-031-19135-0_5">https://doi.org/10.1007/978-3-031-19135-0_5</a>'
  chicago: Bose, Sougata, Thomas A Henzinger, Karoliina Lehtinen, Sven Schewe, and
    Patrick Totzke. “History-Deterministic Timed Automata Are Not Determinizable.”
    In <i>16th International Conference on Reachability Problems</i>, 13608:67–76.
    Springer Nature, 2022. <a href="https://doi.org/10.1007/978-3-031-19135-0_5">https://doi.org/10.1007/978-3-031-19135-0_5</a>.
  ieee: S. Bose, T. A. Henzinger, K. Lehtinen, S. Schewe, and P. Totzke, “History-deterministic
    timed automata are not determinizable,” in <i>16th International Conference on
    Reachability Problems</i>, Kaiserslautern, Germany, 2022, vol. 13608, pp. 67–76.
  ista: 'Bose S, Henzinger TA, Lehtinen K, Schewe S, Totzke P. 2022. History-deterministic
    timed automata are not determinizable. 16th International Conference on Reachability
    Problems. RC: Reachability Problems, LNCS, vol. 13608, 67–76.'
  mla: Bose, Sougata, et al. “History-Deterministic Timed Automata Are Not Determinizable.”
    <i>16th International Conference on Reachability Problems</i>, vol. 13608, Springer
    Nature, 2022, pp. 67–76, doi:<a href="https://doi.org/10.1007/978-3-031-19135-0_5">10.1007/978-3-031-19135-0_5</a>.
  short: S. Bose, T.A. Henzinger, K. Lehtinen, S. Schewe, P. Totzke, in:, 16th International
    Conference on Reachability Problems, Springer Nature, 2022, pp. 67–76.
conference:
  end_date: 2022-10-21
  location: Kaiserslautern, Germany
  name: 'RC: Reachability Problems'
  start_date: 2022-10-17
date_created: 2023-01-12T12:11:57Z
date_published: 2022-10-12T00:00:00Z
date_updated: 2025-09-10T09:50:45Z
day: '12'
department:
- _id: ToHe
doi: 10.1007/978-3-031-19135-0_5
ec_funded: 1
external_id:
  isi:
  - '001333698300005'
intvolume: '     13608'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://hal.science/hal-03849398/
month: '10'
oa: 1
oa_version: Preprint
page: 67-76
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
publication: 16th International Conference on Reachability Problems
publication_identifier:
  eisbn:
  - '9783031191350'
  eissn:
  - 1611-3349
  isbn:
  - '9783031191343'
  issn:
  - 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: History-deterministic timed automata are not determinizable
type: conference
user_id: 317138e5-6ab7-11ef-aa6d-ffef3953e345
volume: 13608
year: '2022'
...
---
_id: '12302'
abstract:
- lang: eng
  text: 'We propose a novel algorithm to decide the language inclusion between (nondeterministic)
    Büchi automata, a PSPACE-complete problem. Our approach, like others before, leverage
    a notion of quasiorder to prune the search for a counterexample by discarding
    candidates which are subsumed by others for the quasiorder. Discarded candidates
    are guaranteed to not compromise the completeness of the algorithm. The novelty
    of our work lies in the quasiorder used to discard candidates. We introduce FORQs
    (family of right quasiorders) that we obtain by adapting the notion of family
    of right congruences put forward by Maler and Staiger in 1993. We define a FORQ-based
    inclusion algorithm which we prove correct and instantiate it for a specific FORQ,
    called the structural FORQ, induced by the Büchi automaton to the right of the
    inclusion sign. The resulting implementation, called FORKLIFT, scales up better
    than the state-of-the-art on a variety of benchmarks including benchmarks from
    program verification and theorem proving for word combinatorics. Artifact: https://doi.org/10.5281/zenodo.6552870'
acknowledgement: This work was partially funded by the ESF Investing in your future,
  the Madrid regional project S2018/TCS-4339 BLOQUES, the Spanish project PGC2018-102210-B-I00
  BOSCO, the Ramón y Cajal fellowship RYC-2016-20281, and the ERC grant PR1001ERC02.
alternative_title:
- LNCS
article_processing_charge: No
arxiv: 1
author:
- first_name: Kyveli
  full_name: Doveri, Kyveli
  last_name: Doveri
- first_name: Pierre
  full_name: Ganty, Pierre
  last_name: Ganty
- first_name: Nicolas Adrien
  full_name: Mazzocchi, Nicolas Adrien
  id: b26baa86-3308-11ec-87b0-8990f34baa85
  last_name: Mazzocchi
citation:
  ama: 'Doveri K, Ganty P, Mazzocchi NA. FORQ-based language inclusion formal testing.
    In: <i>Computer Aided Verification</i>. Vol 13372. Springer Nature; 2022:109-129.
    doi:<a href="https://doi.org/10.1007/978-3-031-13188-2_6">10.1007/978-3-031-13188-2_6</a>'
  apa: 'Doveri, K., Ganty, P., &#38; Mazzocchi, N. A. (2022). FORQ-based language
    inclusion formal testing. In <i>Computer Aided Verification</i> (Vol. 13372, pp.
    109–129). Haifa, Israel: Springer Nature. <a href="https://doi.org/10.1007/978-3-031-13188-2_6">https://doi.org/10.1007/978-3-031-13188-2_6</a>'
  chicago: Doveri, Kyveli, Pierre Ganty, and Nicolas Adrien Mazzocchi. “FORQ-Based
    Language Inclusion Formal Testing.” In <i>Computer Aided Verification</i>, 13372:109–29.
    Springer Nature, 2022. <a href="https://doi.org/10.1007/978-3-031-13188-2_6">https://doi.org/10.1007/978-3-031-13188-2_6</a>.
  ieee: K. Doveri, P. Ganty, and N. A. Mazzocchi, “FORQ-based language inclusion formal
    testing,” in <i>Computer Aided Verification</i>, Haifa, Israel, 2022, vol. 13372,
    pp. 109–129.
  ista: 'Doveri K, Ganty P, Mazzocchi NA. 2022. FORQ-based language inclusion formal
    testing. Computer Aided Verification. CAV: Computer Aided Verification, LNCS,
    vol. 13372, 109–129.'
  mla: Doveri, Kyveli, et al. “FORQ-Based Language Inclusion Formal Testing.” <i>Computer
    Aided Verification</i>, vol. 13372, Springer Nature, 2022, pp. 109–29, doi:<a
    href="https://doi.org/10.1007/978-3-031-13188-2_6">10.1007/978-3-031-13188-2_6</a>.
  short: K. Doveri, P. Ganty, N.A. Mazzocchi, in:, Computer Aided Verification, Springer
    Nature, 2022, pp. 109–129.
conference:
  end_date: 2022-08-10
  location: Haifa, Israel
  name: 'CAV: Computer Aided Verification'
  start_date: 2022-08-07
date_created: 2023-01-16T10:06:31Z
date_published: 2022-08-06T00:00:00Z
date_updated: 2025-04-14T07:55:56Z
day: '06'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.1007/978-3-031-13188-2_6
ec_funded: 1
external_id:
  arxiv:
  - '2207.13549'
  isi:
  - '000870310500006'
file:
- access_level: open_access
  checksum: edc363b1be5447a09063e115c247918a
  content_type: application/pdf
  creator: dernst
  date_created: 2023-01-30T12:51:02Z
  date_updated: 2023-01-30T12:51:02Z
  file_id: '12465'
  file_name: 2022_LNCS_Doveri.pdf
  file_size: 497682
  relation: main_file
  success: 1
file_date_updated: 2023-01-30T12:51:02Z
has_accepted_license: '1'
intvolume: '     13372'
isi: 1
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 109-129
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
publication: Computer Aided Verification
publication_identifier:
  eisbn:
  - '9783031131882'
  eissn:
  - 1611-3349
  isbn:
  - '9783031131875'
  issn:
  - 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: FORQ-based language inclusion formal testing
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 13372
year: '2022'
...
---
_id: '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: <i>47th
    International Symposium on Mathematical Foundations of Computer Science</i>. Vol
    241. Leibniz International Proceedings in Informatics (LIPIcs). Dagstuhl, Germany:
    Schloss Dagstuhl - Leibniz-Zentrum für Informatik; 2022:3:1-3:6. doi:<a href="https://doi.org/10.4230/LIPIcs.MFCS.2022.3">10.4230/LIPIcs.MFCS.2022.3</a>'
  apa: 'Avni, G., &#38; Henzinger, T. A. (2022). An updated survey of bidding games
    on graphs. In <i>47th International Symposium on Mathematical Foundations of Computer
    Science</i> (Vol. 241, p. 3:1-3:6). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum
    für Informatik. <a href="https://doi.org/10.4230/LIPIcs.MFCS.2022.3">https://doi.org/10.4230/LIPIcs.MFCS.2022.3</a>'
  chicago: 'Avni, Guy, and Thomas A Henzinger. “An Updated Survey of Bidding Games
    on Graphs.” In <i>47th International Symposium on Mathematical Foundations of
    Computer Science</i>, 241:3:1-3:6. Leibniz International Proceedings in Informatics
    (LIPIcs). Dagstuhl, Germany: Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
    2022. <a href="https://doi.org/10.4230/LIPIcs.MFCS.2022.3">https://doi.org/10.4230/LIPIcs.MFCS.2022.3</a>.'
  ieee: G. Avni and T. A. Henzinger, “An updated survey of bidding games on graphs,”
    in <i>47th International Symposium on Mathematical Foundations of Computer Science</i>,
    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: 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.” <i>47th International Symposium on Mathematical Foundations of Computer
    Science</i>, vol. 241, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022,
    p. 3:1-3:6, doi:<a href="https://doi.org/10.4230/LIPIcs.MFCS.2022.3">10.4230/LIPIcs.MFCS.2022.3</a>.
  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: Mathematical Foundations of Computer Science'
  start_date: 2022-08-22
corr_author: '1'
date_created: 2023-02-05T17:26:01Z
date_published: 2022-08-22T00:00:00Z
date_updated: 2025-07-10T11:50:27Z
day: '22'
ddc:
- '000'
department:
- _id: ToHe
doi: 10.4230/LIPIcs.MFCS.2022.3
ec_funded: 1
file:
- access_level: open_access
  checksum: 1888ec9421622f9526fbec2de035f132
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  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: '12510'
abstract:
- lang: eng
  text: "We introduce a new statistical verification algorithm that formally quantifies
    the behavioral robustness of any time-continuous process formulated as a continuous-depth
    model. Our algorithm solves a set of global optimization (Go) problems over a
    given time horizon to construct a tight enclosure (Tube) of the set of all process
    executions starting from a ball of initial states. We call our algorithm GoTube.
    Through its construction, GoTube ensures that the bounding tube is conservative
    up to a desired probability and up to a desired tightness.\r\n GoTube is implemented
    in JAX and optimized to scale to complex continuous-depth neural network models.
    Compared to advanced reachability analysis tools for time-continuous neural networks,
    GoTube does not accumulate overapproximation errors between time steps and avoids
    the infamous wrapping effect inherent in symbolic techniques. We show that GoTube
    substantially outperforms state-of-the-art verification tools in terms of the
    size of the initial ball, speed, time-horizon, task completion, and scalability
    on a large set of experiments.\r\n GoTube is stable and sets the state-of-the-art
    in terms of its ability to scale to time horizons well beyond what has been previously
    possible."
acknowledgement: SG is funded by the Austrian Science Fund (FWF) project number W1255-N23.
  ML and TH are supported in part by FWF under grant Z211-N23 (Wittgenstein Award)
  and the ERC-2020-AdG 101020093. SS is supported by NSF awards DCL-2040599, CCF-1918225,
  and CPS-1446832. RH and DR are partially supported by Boeing. RG is partially supported
  by Horizon-2020 ECSEL Project grant No. 783163 (iDev40).
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Sophie A.
  full_name: Gruenbacher, Sophie A.
  last_name: Gruenbacher
- first_name: Mathias
  full_name: Lechner, Mathias
  id: 3DC22916-F248-11E8-B48F-1D18A9856A87
  last_name: Lechner
- first_name: Ramin
  full_name: Hasani, Ramin
  last_name: Hasani
- first_name: Daniela
  full_name: Rus, Daniela
  last_name: Rus
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
- first_name: Scott A.
  full_name: Smolka, Scott A.
  last_name: Smolka
- first_name: Radu
  full_name: Grosu, Radu
  last_name: Grosu
citation:
  ama: 'Gruenbacher SA, Lechner M, Hasani R, et al. GoTube: Scalable statistical verification
    of continuous-depth models. <i>Proceedings of the AAAI Conference on Artificial
    Intelligence</i>. 2022;36(6):6755-6764. doi:<a href="https://doi.org/10.1609/aaai.v36i6.20631">10.1609/aaai.v36i6.20631</a>'
  apa: 'Gruenbacher, S. A., Lechner, M., Hasani, R., Rus, D., Henzinger, T. A., Smolka,
    S. A., &#38; Grosu, R. (2022). GoTube: Scalable statistical verification of continuous-depth
    models. <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>.
    Association for the Advancement of Artificial Intelligence. <a href="https://doi.org/10.1609/aaai.v36i6.20631">https://doi.org/10.1609/aaai.v36i6.20631</a>'
  chicago: 'Gruenbacher, Sophie A., Mathias Lechner, Ramin Hasani, Daniela Rus, Thomas
    A Henzinger, Scott A. Smolka, and Radu Grosu. “GoTube: Scalable Statistical Verification
    of Continuous-Depth Models.” <i>Proceedings of the AAAI Conference on Artificial
    Intelligence</i>. Association for the Advancement of Artificial Intelligence,
    2022. <a href="https://doi.org/10.1609/aaai.v36i6.20631">https://doi.org/10.1609/aaai.v36i6.20631</a>.'
  ieee: 'S. A. Gruenbacher <i>et al.</i>, “GoTube: Scalable statistical verification
    of continuous-depth models,” <i>Proceedings of the AAAI Conference on Artificial
    Intelligence</i>, vol. 36, no. 6. Association for the Advancement of Artificial
    Intelligence, pp. 6755–6764, 2022.'
  ista: 'Gruenbacher SA, Lechner M, Hasani R, Rus D, Henzinger TA, Smolka SA, Grosu
    R. 2022. GoTube: Scalable statistical verification of continuous-depth models.
    Proceedings of the AAAI Conference on Artificial Intelligence. 36(6), 6755–6764.'
  mla: 'Gruenbacher, Sophie A., et al. “GoTube: Scalable Statistical Verification
    of Continuous-Depth Models.” <i>Proceedings of the AAAI Conference on Artificial
    Intelligence</i>, vol. 36, no. 6, Association for the Advancement of Artificial
    Intelligence, 2022, pp. 6755–64, doi:<a href="https://doi.org/10.1609/aaai.v36i6.20631">10.1609/aaai.v36i6.20631</a>.'
  short: S.A. Gruenbacher, M. Lechner, R. Hasani, D. Rus, T.A. Henzinger, S.A. Smolka,
    R. Grosu, Proceedings of the AAAI Conference on Artificial Intelligence 36 (2022)
    6755–6764.
date_created: 2023-02-05T17:27:42Z
date_published: 2022-06-28T00:00:00Z
date_updated: 2025-04-15T06:26:14Z
day: '28'
department:
- _id: ToHe
doi: 10.1609/aaai.v36i6.20631
ec_funded: 1
external_id:
  arxiv:
  - '2107.08467'
intvolume: '        36'
issue: '6'
keyword:
- General Medicine
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/2107.08467
month: '06'
oa: 1
oa_version: Preprint
page: 6755-6764
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
  call_identifier: FWF
  grant_number: Z211
  name: Formal methods for the design and analysis of complex systems
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
publication: Proceedings of the AAAI Conference on Artificial Intelligence
publication_identifier:
  eissn:
  - 2374-3468
  isbn:
  - '978577358350'
  issn:
  - 2159-5399
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'GoTube: Scalable statistical verification of continuous-depth models'
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 36
year: '2022'
...
---
_id: '12511'
abstract:
- lang: eng
  text: "We consider the problem of formally verifying almost-sure (a.s.) asymptotic
    stability in discrete-time nonlinear stochastic control systems. While verifying
    stability in deterministic control systems is extensively studied in the literature,
    verifying stability in stochastic control systems is an open problem. The few
    existing works on this topic either consider only specialized forms of stochasticity
    or make restrictive assumptions on the system, rendering them inapplicable to
    learning algorithms with neural network policies. \r\n In this work, we present
    an approach for general nonlinear stochastic control problems with two novel aspects:
    (a) instead of classical stochastic extensions of Lyapunov functions, we use ranking
    supermartingales (RSMs) to certify a.s. asymptotic stability, and (b) we present
    a method for learning neural network RSMs. \r\n We prove that our approach guarantees
    a.s. asymptotic stability of the system and\r\n provides the first method to obtain
    bounds on the stabilization time, which stochastic Lyapunov functions do not.\r\n
    Finally, we validate our approach experimentally on a set of nonlinear stochastic
    reinforcement learning environments with neural network policies."
acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093, ERC
  CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
  programme\r\nunder the Marie Skłodowska-Curie Grant Agreement No. 665385."
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Mathias
  full_name: Lechner, Mathias
  id: 3DC22916-F248-11E8-B48F-1D18A9856A87
  last_name: Lechner
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
citation:
  ama: Lechner M, Zikelic D, Chatterjee K, Henzinger TA. Stability verification in
    stochastic control systems via neural network supermartingales. <i>Proceedings
    of the AAAI Conference on Artificial Intelligence</i>. 2022;36(7):7326-7336. doi:<a
    href="https://doi.org/10.1609/aaai.v36i7.20695">10.1609/aaai.v36i7.20695</a>
  apa: Lechner, M., Zikelic, D., Chatterjee, K., &#38; Henzinger, T. A. (2022). Stability
    verification in stochastic control systems via neural network supermartingales.
    <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Association
    for the Advancement of Artificial Intelligence. <a href="https://doi.org/10.1609/aaai.v36i7.20695">https://doi.org/10.1609/aaai.v36i7.20695</a>
  chicago: Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, and Thomas A Henzinger.
    “Stability Verification in Stochastic Control Systems via Neural Network Supermartingales.”
    <i>Proceedings of the AAAI Conference on Artificial Intelligence</i>. Association
    for the Advancement of Artificial Intelligence, 2022. <a href="https://doi.org/10.1609/aaai.v36i7.20695">https://doi.org/10.1609/aaai.v36i7.20695</a>.
  ieee: M. Lechner, D. Zikelic, K. Chatterjee, and T. A. Henzinger, “Stability verification
    in stochastic control systems via neural network supermartingales,” <i>Proceedings
    of the AAAI Conference on Artificial Intelligence</i>, vol. 36, no. 7. Association
    for the Advancement of Artificial Intelligence, pp. 7326–7336, 2022.
  ista: Lechner M, Zikelic D, Chatterjee K, Henzinger TA. 2022. Stability verification
    in stochastic control systems via neural network supermartingales. Proceedings
    of the AAAI Conference on Artificial Intelligence. 36(7), 7326–7336.
  mla: Lechner, Mathias, et al. “Stability Verification in Stochastic Control Systems
    via Neural Network Supermartingales.” <i>Proceedings of the AAAI Conference on
    Artificial Intelligence</i>, vol. 36, no. 7, Association for the Advancement of
    Artificial Intelligence, 2022, pp. 7326–36, doi:<a href="https://doi.org/10.1609/aaai.v36i7.20695">10.1609/aaai.v36i7.20695</a>.
  short: M. Lechner, D. Zikelic, K. Chatterjee, T.A. Henzinger, Proceedings of the
    AAAI Conference on Artificial Intelligence 36 (2022) 7326–7336.
corr_author: '1'
date_created: 2023-02-05T17:29:50Z
date_published: 2022-06-28T00:00:00Z
date_updated: 2026-04-07T13:27:55Z
day: '28'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v36i7.20695
ec_funded: 1
external_id:
  arxiv:
  - '2112.09495'
intvolume: '        36'
issue: '7'
keyword:
- General Medicine
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://arxiv.org/abs/2112.09495
month: '06'
oa: 1
oa_version: Preprint
page: 7326-7336
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication: Proceedings of the AAAI Conference on Artificial Intelligence
publication_identifier:
  eissn:
  - 2374-3468
  isbn:
  - '9781577358350'
  issn:
  - 2159-5399
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
related_material:
  record:
  - id: '14539'
    relation: dissertation_contains
    status: public
scopus_import: '1'
status: public
title: Stability verification in stochastic control systems via neural network supermartingales
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 36
year: '2022'
...
