---
_id: '14317'
abstract:
- lang: eng
text: "Markov decision processes can be viewed as transformers of probability distributions.
While this view is useful from a practical standpoint to reason about trajectories
of distributions, basic reachability and safety problems are known to be computationally
intractable (i.e., Skolem-hard) to solve in such models. Further, we show that
even for simple examples of MDPs, strategies for safety objectives over distributions
can require infinite memory and randomization.\r\nIn light of this, we present
a novel overapproximation approach to synthesize strategies in an MDP, such that
a safety objective over the distributions is met. More precisely, we develop a
new framework for template-based synthesis of certificates as affine distributional
and inductive invariants for safety objectives in MDPs. We provide two algorithms
within this framework. One can only synthesize memoryless strategies, but has
relative completeness guarantees, while the other can synthesize general strategies.
The runtime complexity of both algorithms is in PSPACE. We implement these algorithms
and show that they can solve several non-trivial examples."
acknowledgement: This work was supported in part 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 as well as DST/CEFIPRA/INRIA project
EQuaVE and SERB Matrices grant MTR/2018/00074.
alternative_title:
- LNCS
article_processing_charge: Yes (in subscription journal)
author:
- first_name: S.
full_name: Akshay, S.
last_name: Akshay
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Akshay S, Chatterjee K, Meggendorfer T, Zikelic D. MDPs as distribution transformers:
Affine invariant synthesis for safety objectives. In: International Conference
on Computer Aided Verification. Vol 13966. Springer Nature; 2023:86-112. doi:10.1007/978-3-031-37709-9_5'
apa: 'Akshay, S., Chatterjee, K., Meggendorfer, T., & Zikelic, D. (2023). MDPs
as distribution transformers: Affine invariant synthesis for safety objectives.
In International Conference on Computer Aided Verification (Vol. 13966,
pp. 86–112). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-37709-9_5'
chicago: 'Akshay, S., Krishnendu Chatterjee, Tobias Meggendorfer, and Dorde Zikelic.
“MDPs as Distribution Transformers: Affine Invariant Synthesis for Safety Objectives.”
In International Conference on Computer Aided Verification, 13966:86–112.
Springer Nature, 2023. https://doi.org/10.1007/978-3-031-37709-9_5.'
ieee: 'S. Akshay, K. Chatterjee, T. Meggendorfer, and D. Zikelic, “MDPs as distribution
transformers: Affine invariant synthesis for safety objectives,” in International
Conference on Computer Aided Verification, Paris, France, 2023, vol. 13966,
pp. 86–112.'
ista: 'Akshay S, Chatterjee K, Meggendorfer T, Zikelic D. 2023. MDPs as distribution
transformers: Affine invariant synthesis for safety objectives. International
Conference on Computer Aided Verification. CAV: Computer Aided Verification, LNCS,
vol. 13966, 86–112.'
mla: 'Akshay, S., et al. “MDPs as Distribution Transformers: Affine Invariant Synthesis
for Safety Objectives.” International Conference on Computer Aided Verification,
vol. 13966, Springer Nature, 2023, pp. 86–112, doi:10.1007/978-3-031-37709-9_5.'
short: S. Akshay, K. Chatterjee, T. Meggendorfer, D. Zikelic, in:, International
Conference on Computer Aided Verification, Springer Nature, 2023, pp. 86–112.
conference:
end_date: 2023-07-22
location: Paris, France
name: 'CAV: Computer Aided Verification'
start_date: 2023-07-17
date_created: 2023-09-10T22:01:12Z
date_published: 2023-07-17T00:00:00Z
date_updated: 2025-07-14T09:09:56Z
day: '17'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/978-3-031-37709-9_5
ec_funded: 1
file:
- access_level: open_access
checksum: f143c8eedf609f20f2aad2eeb496d53f
content_type: application/pdf
creator: dernst
date_created: 2023-09-20T08:46:43Z
date_updated: 2023-09-20T08:46:43Z
file_id: '14349'
file_name: 2023_LNCS_Akshay.pdf
file_size: 531745
relation: main_file
success: 1
file_date_updated: 2023-09-20T08:46:43Z
has_accepted_license: '1'
intvolume: ' 13966'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 86-112
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: International Conference on Computer Aided Verification
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031377082'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'MDPs as distribution transformers: Affine invariant synthesis for safety objectives'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13966
year: '2023'
...
---
_id: '14518'
abstract:
- lang: eng
text: We consider bidding games, a class of two-player zero-sum graph games. The
game proceeds as follows. Both players have bounded budgets. A token is placed
on a vertex of a graph, in each turn the players simultaneously submit bids, and
the higher bidder moves the token, where we break bidding ties in favor of Player
1. Player 1 wins the game iff the token visits a designated target vertex. We
consider, for the first time, poorman discrete-bidding in which the granularity
of the bids is restricted and the higher bid is paid to the bank. Previous work
either did not impose granularity restrictions or considered Richman bidding (bids
are paid to the opponent). While the latter mechanisms are technically more accessible,
the former is more appealing from a practical standpoint. Our study focuses on
threshold budgets, which is the necessary and sufficient initial budget required
for Player 1 to ensure winning against a given Player 2 budget. We first show
existence of thresholds. In DAGs, we show that threshold budgets can be approximated
with error bounds by thresholds under continuous-bidding and that they exhibit
a periodic behavior. We identify closed-form solutions in special cases. We implement
and experiment with an algorithm to find threshold budgets.
acknowledgement: This research was supported in part by ISF grant no. 1679/21, ERC
CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
programme under the Marie SkłodowskaCurie Grant Agreement No. 665385.
article_processing_charge: No
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: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
- first_name: Suman
full_name: Sadhukhan, Suman
last_name: Sadhukhan
- first_name: Josef
full_name: Tkadlec, Josef
id: 3F24CCC8-F248-11E8-B48F-1D18A9856A87
last_name: Tkadlec
orcid: 0000-0002-1097-9684
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Avni G, Meggendorfer T, Sadhukhan S, Tkadlec J, Zikelic D. Reachability poorman
discrete-bidding games. In: Frontiers in Artificial Intelligence and Applications.
Vol 372. IOS Press; 2023:141-148. doi:10.3233/FAIA230264'
apa: 'Avni, G., Meggendorfer, T., Sadhukhan, S., Tkadlec, J., & Zikelic, D.
(2023). Reachability poorman discrete-bidding games. In Frontiers in Artificial
Intelligence and Applications (Vol. 372, pp. 141–148). Krakow, Poland: IOS
Press. https://doi.org/10.3233/FAIA230264'
chicago: Avni, Guy, Tobias Meggendorfer, Suman Sadhukhan, Josef Tkadlec, and Dorde
Zikelic. “Reachability Poorman Discrete-Bidding Games.” In Frontiers in Artificial
Intelligence and Applications, 372:141–48. IOS Press, 2023. https://doi.org/10.3233/FAIA230264.
ieee: G. Avni, T. Meggendorfer, S. Sadhukhan, J. Tkadlec, and D. Zikelic, “Reachability
poorman discrete-bidding games,” in Frontiers in Artificial Intelligence and
Applications, Krakow, Poland, 2023, vol. 372, pp. 141–148.
ista: 'Avni G, Meggendorfer T, Sadhukhan S, Tkadlec J, Zikelic D. 2023. Reachability
poorman discrete-bidding games. Frontiers in Artificial Intelligence and Applications.
ECAI: European Conference on Artificial Intelligence vol. 372, 141–148.'
mla: Avni, Guy, et al. “Reachability Poorman Discrete-Bidding Games.” Frontiers
in Artificial Intelligence and Applications, vol. 372, IOS Press, 2023, pp.
141–48, doi:10.3233/FAIA230264.
short: G. Avni, T. Meggendorfer, S. Sadhukhan, J. Tkadlec, D. Zikelic, in:, Frontiers
in Artificial Intelligence and Applications, IOS Press, 2023, pp. 141–148.
conference:
end_date: 2023-10-04
location: Krakow, Poland
name: 'ECAI: European Conference on Artificial Intelligence'
start_date: 2023-09-30
date_created: 2023-11-12T23:00:56Z
date_published: 2023-09-28T00:00:00Z
date_updated: 2025-07-14T09:09:57Z
day: '28'
ddc:
- '000'
department:
- _id: ToHe
- _id: KrCh
doi: 10.3233/FAIA230264
ec_funded: 1
external_id:
arxiv:
- '2307.15218'
file:
- access_level: open_access
checksum: 1390ca38480fa4cf286b0f1a42e8c12f
content_type: application/pdf
creator: dernst
date_created: 2023-11-13T10:16:10Z
date_updated: 2023-11-13T10:16:10Z
file_id: '14529'
file_name: 2023_FAIA_Avni.pdf
file_size: 501011
relation: main_file
success: 1
file_date_updated: 2023-11-13T10:16:10Z
has_accepted_license: '1'
intvolume: ' 372'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc/4.0/
month: '09'
oa: 1
oa_version: Published Version
page: 141-148
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Frontiers in Artificial Intelligence and Applications
publication_identifier:
isbn:
- '9781643684369'
issn:
- 0922-6389
publication_status: published
publisher: IOS Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Reachability poorman discrete-bidding games
tmp:
image: /images/cc_by_nc.png
legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode
name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
short: CC BY-NC (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 372
year: '2023'
...
---
_id: '14539'
abstract:
- lang: eng
text: "Stochastic systems provide a formal framework for modelling and quantifying
uncertainty in systems and have been widely adopted in many application domains.
Formal\r\nverification and control of finite state stochastic systems, a subfield
of formal methods\r\nalso known as probabilistic model checking, is well studied.
In contrast, formal verification and control of infinite state stochastic systems
have received comparatively\r\nless attention. However, infinite state stochastic
systems commonly arise in practice.\r\nFor instance, probabilistic models that
contain continuous probability distributions such\r\nas normal or uniform, or
stochastic dynamical systems which are a classical model for\r\ncontrol under
uncertainty, both give rise to infinite state systems.\r\nThe goal of this thesis
is to contribute to laying theoretical and algorithmic foundations\r\nof fully
automated formal verification and control of infinite state stochastic systems,\r\nwith
a particular focus on systems that may be executed over a long or infinite time.\r\nWe
consider formal verification of infinite state stochastic systems in the setting
of\r\nstatic analysis of probabilistic programs and formal control in the setting
of controller\r\nsynthesis in stochastic dynamical systems. For both problems,
we present some of the\r\nfirst fully automated methods for probabilistic (a.k.a.
quantitative) reachability and\r\nsafety analysis applicable to infinite time
horizon systems. We also advance the state\r\nof the art of probability 1 (a.k.a.
qualitative) reachability analysis for both problems.\r\nFinally, for formal controller
synthesis in stochastic dynamical systems, we present a\r\nnovel framework for
learning neural network control policies in stochastic dynamical\r\nsystems with
formal guarantees on correctness with respect to quantitative reachability,\r\nsafety
or reach-avoid specifications.\r\n"
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: Zikelic D. Automated verification and control of infinite state stochastic
systems. 2023. doi:10.15479/14539
apa: Zikelic, D. (2023). Automated verification and control of infinite state
stochastic systems. Institute of Science and Technology Austria. https://doi.org/10.15479/14539
chicago: Zikelic, Dorde. “Automated Verification and Control of Infinite State Stochastic
Systems.” Institute of Science and Technology Austria, 2023. https://doi.org/10.15479/14539.
ieee: D. Zikelic, “Automated verification and control of infinite state stochastic
systems,” Institute of Science and Technology Austria, 2023.
ista: Zikelic D. 2023. Automated verification and control of infinite state stochastic
systems. Institute of Science and Technology Austria.
mla: Zikelic, Dorde. Automated Verification and Control of Infinite State Stochastic
Systems. Institute of Science and Technology Austria, 2023, doi:10.15479/14539.
short: D. Zikelic, Automated Verification and Control of Infinite State Stochastic
Systems, Institute of Science and Technology Austria, 2023.
date_created: 2023-11-15T13:39:10Z
date_published: 2023-11-15T00:00:00Z
date_updated: 2025-07-14T09:10:10Z
day: '15'
ddc:
- '000'
degree_awarded: PhD
department:
- _id: KrCh
- _id: GradSch
doi: 10.15479/14539
ec_funded: 1
file:
- access_level: open_access
checksum: f23e002b0059ca78e1fbb864da52dd7e
content_type: application/pdf
creator: cchlebak
date_created: 2023-11-15T13:43:28Z
date_updated: 2023-11-15T13:43:28Z
file_id: '14540'
file_name: main.pdf
file_size: 2116426
relation: main_file
success: 1
- access_level: closed
checksum: 80ca37618a3c7b59866875f8be9b15ed
content_type: application/x-zip-compressed
creator: cchlebak
date_created: 2023-11-15T13:44:24Z
date_updated: 2023-11-15T13:44:24Z
file_id: '14541'
file_name: thesis_source.zip
file_size: 35884057
relation: source_file
file_date_updated: 2023-11-15T13:44:24Z
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-sa/4.0/
month: '11'
oa: 1
oa_version: Published Version
page: '256'
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_identifier:
isbn:
- 978-3-99078-036-7
issn:
- 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
record:
- id: '1194'
relation: part_of_dissertation
status: public
- id: '12000'
relation: part_of_dissertation
status: public
- id: '12511'
relation: part_of_dissertation
status: public
- id: '14600'
relation: part_of_dissertation
status: public
- id: '14601'
relation: part_of_dissertation
status: public
- id: '9644'
relation: part_of_dissertation
status: public
- id: '10414'
relation: part_of_dissertation
status: public
status: public
supervisor:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
title: Automated verification and control of infinite state stochastic systems
tmp:
image: /images/cc_by_nc_sa.png
legal_code_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC
BY-NC-SA 4.0)
short: CC BY-NC-SA (4.0)
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '14559'
abstract:
- lang: eng
text: We consider the problem of learning control policies in discrete-time stochastic
systems which guarantee that the system stabilizes within some specified stabilization
region with probability 1. Our approach is based on the novel notion of stabilizing
ranking supermartingales (sRSMs) that we introduce in this work. Our sRSMs overcome
the limitation of methods proposed in previous works whose applicability is restricted
to systems in which the stabilizing region cannot be left once entered under any
control policy. We present a learning procedure that learns a control policy together
with an sRSM that formally certifies probability 1 stability, both learned as
neural networks. We show that this procedure can also be adapted to formally verifying
that, under a given Lipschitz continuous control policy, the stochastic system
stabilizes within some stabilizing region with probability 1. Our experimental
evaluation shows that our learning procedure can successfully learn provably stabilizing
policies in practice.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC
CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Matin
full_name: Ansaripour, Matin
last_name: Ansaripour
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Ansaripour M, Chatterjee K, Henzinger TA, Lechner M, Zikelic D. Learning provably
stabilizing neural controllers for discrete-time stochastic systems. In: 21st
International Symposium on Automated Technology for Verification and Analysis.
Vol 14215. Springer Nature; 2023:357-379. doi:10.1007/978-3-031-45329-8_17'
apa: 'Ansaripour, M., Chatterjee, K., Henzinger, T. A., Lechner, M., & Zikelic,
D. (2023). Learning provably stabilizing neural controllers for discrete-time
stochastic systems. In 21st International Symposium on Automated Technology
for Verification and Analysis (Vol. 14215, pp. 357–379). Singapore, Singapore:
Springer Nature. https://doi.org/10.1007/978-3-031-45329-8_17'
chicago: Ansaripour, Matin, Krishnendu Chatterjee, Thomas A Henzinger, Mathias Lechner,
and Dorde Zikelic. “Learning Provably Stabilizing Neural Controllers for Discrete-Time
Stochastic Systems.” In 21st International Symposium on Automated Technology
for Verification and Analysis, 14215:357–79. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-45329-8_17.
ieee: M. Ansaripour, K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic,
“Learning provably stabilizing neural controllers for discrete-time stochastic
systems,” in 21st International Symposium on Automated Technology for Verification
and Analysis, Singapore, Singapore, 2023, vol. 14215, pp. 357–379.
ista: 'Ansaripour M, Chatterjee K, Henzinger TA, Lechner M, Zikelic D. 2023. Learning
provably stabilizing neural controllers for discrete-time stochastic systems.
21st International Symposium on Automated Technology for Verification and Analysis.
ATVA: Automated Technology for Verification and Analysis, LNCS, vol. 14215, 357–379.'
mla: Ansaripour, Matin, et al. “Learning Provably Stabilizing Neural Controllers
for Discrete-Time Stochastic Systems.” 21st International Symposium on Automated
Technology for Verification and Analysis, vol. 14215, Springer Nature, 2023,
pp. 357–79, doi:10.1007/978-3-031-45329-8_17.
short: M. Ansaripour, K. Chatterjee, T.A. Henzinger, M. Lechner, D. Zikelic, in:,
21st International Symposium on Automated Technology for Verification and Analysis,
Springer Nature, 2023, pp. 357–379.
conference:
end_date: 2023-10-27
location: Singapore, Singapore
name: 'ATVA: Automated Technology for Verification and Analysis'
start_date: 2023-10-24
date_created: 2023-11-19T23:00:56Z
date_published: 2023-10-22T00:00:00Z
date_updated: 2025-07-14T09:09:59Z
day: '22'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1007/978-3-031-45329-8_17
ec_funded: 1
intvolume: ' 14215'
language:
- iso: eng
month: '10'
oa_version: None
page: 357-379
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: 21st International Symposium on Automated Technology for Verification
and Analysis
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031453281'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Learning provably stabilizing neural controllers for discrete-time stochastic
systems
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14215
year: '2023'
...
---
_id: '14778'
abstract:
- lang: eng
text: 'We consider the almost-sure (a.s.) termination problem for probabilistic
programs, which are a stochastic extension of classical imperative programs. Lexicographic
ranking functions provide a sound and practical approach for termination of non-probabilistic
programs, and their extension to probabilistic programs is achieved via lexicographic
ranking supermartingales (LexRSMs). However, LexRSMs introduced in the previous
work have a limitation that impedes their automation: all of their components
have to be non-negative in all reachable states. This might result in a LexRSM
not existing even for simple terminating programs. Our contributions are twofold.
First, we introduce a generalization of LexRSMs that allows for some components
to be negative. This standard feature of non-probabilistic termination proofs
was hitherto not known to be sound in the probabilistic setting, as the soundness
proof requires a careful analysis of the underlying stochastic process. Second,
we present polynomial-time algorithms using our generalized LexRSMs for proving
a.s. termination in broad classes of linear-arithmetic programs.'
acknowledgement: This research was partially supported by the ERC CoG (grant no. 863818;
ForM-SMArt), the Czech Science Foundation (grant no. GA21-24711S), and the European
Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie
Grant Agreement No. 665385.
article_number: '11'
article_processing_charge: Yes (via OA deal)
article_type: original
arxiv: 1
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Ehsan
full_name: Kafshdar Goharshady, Ehsan
last_name: Kafshdar Goharshady
- first_name: Petr
full_name: Novotný, Petr
id: 3CC3B868-F248-11E8-B48F-1D18A9856A87
last_name: Novotný
- first_name: Jiří
full_name: Zárevúcky, Jiří
last_name: Zárevúcky
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: Chatterjee K, Kafshdar Goharshady E, Novotný P, Zárevúcky J, Zikelic D. On
lexicographic proof rules for probabilistic termination. Formal Aspects of
Computing. 2023;35(2). doi:10.1145/3585391
apa: Chatterjee, K., Kafshdar Goharshady, E., Novotný, P., Zárevúcky, J., &
Zikelic, D. (2023). On lexicographic proof rules for probabilistic termination.
Formal Aspects of Computing. Association for Computing Machinery. https://doi.org/10.1145/3585391
chicago: Chatterjee, Krishnendu, Ehsan Kafshdar Goharshady, Petr Novotný, Jiří Zárevúcky,
and Dorde Zikelic. “On Lexicographic Proof Rules for Probabilistic Termination.”
Formal Aspects of Computing. Association for Computing Machinery, 2023.
https://doi.org/10.1145/3585391.
ieee: K. Chatterjee, E. Kafshdar Goharshady, P. Novotný, J. Zárevúcky, and D. Zikelic,
“On lexicographic proof rules for probabilistic termination,” Formal Aspects
of Computing, vol. 35, no. 2. Association for Computing Machinery, 2023.
ista: Chatterjee K, Kafshdar Goharshady E, Novotný P, Zárevúcky J, Zikelic D. 2023.
On lexicographic proof rules for probabilistic termination. Formal Aspects of
Computing. 35(2), 11.
mla: Chatterjee, Krishnendu, et al. “On Lexicographic Proof Rules for Probabilistic
Termination.” Formal Aspects of Computing, vol. 35, no. 2, 11, Association
for Computing Machinery, 2023, doi:10.1145/3585391.
short: K. Chatterjee, E. Kafshdar Goharshady, P. Novotný, J. Zárevúcky, D. Zikelic,
Formal Aspects of Computing 35 (2023).
date_created: 2024-01-10T09:27:43Z
date_published: 2023-06-23T00:00:00Z
date_updated: 2025-07-14T09:10:10Z
day: '23'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1145/3585391
ec_funded: 1
external_id:
arxiv:
- '2108.02188'
file:
- access_level: open_access
checksum: 3bb133eeb27ec01649a9a36445d952d9
content_type: application/pdf
creator: dernst
date_created: 2024-01-16T08:11:24Z
date_updated: 2024-01-16T08:11:24Z
file_id: '14804'
file_name: 2023_FormalAspectsComputing_Chatterjee.pdf
file_size: 502522
relation: main_file
success: 1
file_date_updated: 2024-01-16T08:11:24Z
has_accepted_license: '1'
intvolume: ' 35'
issue: '2'
keyword:
- Theoretical Computer Science
- Software
language:
- iso: eng
month: '06'
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: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Formal Aspects of Computing
publication_identifier:
eissn:
- 1433-299X
issn:
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publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
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relation: earlier_version
status: public
status: public
title: On lexicographic proof rules for probabilistic termination
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: 35
year: '2023'
...
---
_id: '14830'
abstract:
- lang: eng
text: We study the problem of learning controllers for discrete-time non-linear
stochastic dynamical systems with formal reach-avoid guarantees. This work presents
the first method for providing formal reach-avoid guarantees, which combine and
generalize stability and safety guarantees, with a tolerable probability threshold
p in [0,1] over the infinite time horizon. Our method leverages advances in machine
learning literature and it represents formal certificates as neural networks.
In particular, we learn a certificate in the form of a reach-avoid supermartingale
(RASM), a novel notion that we introduce in this work. Our RASMs provide reachability
and avoidance guarantees by imposing constraints on what can be viewed as a stochastic
extension of level sets of Lyapunov functions for deterministic systems. Our approach
solves several important problems -- it can be used to learn a control policy
from scratch, to verify a reach-avoid specification for a fixed control policy,
or to fine-tune a pre-trained policy if it does not satisfy the reach-avoid specification.
We validate our approach on 3 stochastic non-linear reinforcement learning tasks.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC
CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
article_processing_charge: No
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: Proceedings of the
37th AAAI Conference on Artificial Intelligence. Vol 37. Association for the
Advancement of Artificial Intelligence; 2023:11926-11935. doi:10.1609/aaai.v37i10.26407'
apa: 'Zikelic, D., Lechner, M., Henzinger, T. A., & Chatterjee, K. (2023). Learning
control policies for stochastic systems with reach-avoid guarantees. In Proceedings
of the 37th AAAI Conference on Artificial Intelligence (Vol. 37, pp. 11926–11935).
Washington, DC, United States: Association for the Advancement of Artificial Intelligence.
https://doi.org/10.1609/aaai.v37i10.26407'
chicago: Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee.
“Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.”
In Proceedings of the 37th AAAI Conference on Artificial Intelligence,
37:11926–35. Association for the Advancement of Artificial Intelligence, 2023.
https://doi.org/10.1609/aaai.v37i10.26407.
ieee: D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control
policies for stochastic systems with reach-avoid guarantees,” in Proceedings
of the 37th AAAI Conference on Artificial Intelligence, Washington, DC, United
States, 2023, vol. 37, no. 10, pp. 11926–11935.
ista: 'Zikelic D, Lechner M, Henzinger TA, Chatterjee K. 2023. Learning control
policies for stochastic systems with reach-avoid guarantees. Proceedings of the
37th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial
Intelligence vol. 37, 11926–11935.'
mla: Zikelic, Dorde, et al. “Learning Control Policies for Stochastic Systems with
Reach-Avoid Guarantees.” Proceedings of the 37th AAAI Conference on Artificial
Intelligence, vol. 37, no. 10, Association for the Advancement of Artificial
Intelligence, 2023, pp. 11926–35, doi:10.1609/aaai.v37i10.26407.
short: D. Zikelic, M. Lechner, T.A. Henzinger, K. Chatterjee, in:, Proceedings of
the 37th AAAI Conference on Artificial Intelligence, Association for the Advancement
of Artificial Intelligence, 2023, pp. 11926–11935.
conference:
end_date: 2023-02-14
location: Washington, DC, United States
name: 'AAAI: Conference on Artificial Intelligence'
start_date: 2023-02-07
date_created: 2024-01-18T07:44:31Z
date_published: 2023-06-26T00:00:00Z
date_updated: 2025-07-14T09:10:02Z
day: '26'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v37i10.26407
ec_funded: 1
external_id:
arxiv:
- '2210.05308'
intvolume: ' 37'
issue: '10'
keyword:
- General Medicine
language:
- iso: eng
month: '06'
oa_version: Preprint
page: 11926-11935
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Proceedings of the 37th AAAI Conference on Artificial Intelligence
publication_identifier:
eissn:
- 2374-3468
issn:
- 2159-5399
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
related_material:
record:
- id: '14600'
relation: earlier_version
status: public
status: public
title: Learning control policies for stochastic systems with reach-avoid guarantees
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2023'
...
---
_id: '15023'
abstract:
- lang: eng
text: Reinforcement learning has shown promising results in learning neural network
policies for complicated control tasks. However, the lack of formal guarantees
about the behavior of such policies remains an impediment to their deployment.
We propose a novel method for learning a composition of neural network policies
in stochastic environments, along with a formal certificate which guarantees that
a specification over the policy's behavior is satisfied with the desired probability.
Unlike prior work on verifiable RL, our approach leverages the compositional nature
of logical specifications provided in SpectRL, to learn over graphs of probabilistic
reach-avoid specifications. The formal guarantees are provided by learning neural
network policies together with reach-avoid supermartingales (RASM) for the graph’s
sub-tasks and then composing them into a global policy. We also derive a tighter
lower bound compared to previous work on the probability of reach-avoidance implied
by a RASM, which is required to find a compositional policy with an acceptable
probabilistic threshold for complex tasks with multiple edge policies. We implement
a prototype of our approach and evaluate it on a Stochastic Nine Rooms environment.
acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093 (VAMOS)
and the ERC-2020-\r\nCoG 863818 (FoRM-SMArt)."
article_processing_charge: No
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: 37th Conference
on Neural Information Processing Systems. ; 2023.'
apa: Zikelic, D., Lechner, M., Verma, A., Chatterjee, K., & Henzinger, T. A.
(2023). Compositional policy learning in stochastic control systems with formal
guarantees. In 37th Conference on Neural Information Processing Systems.
New Orleans, LO, United States.
chicago: Zikelic, Dorde, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee,
and Thomas A Henzinger. “Compositional Policy Learning in Stochastic Control Systems
with Formal Guarantees.” In 37th Conference on Neural Information Processing
Systems, 2023.
ieee: D. Zikelic, M. Lechner, A. Verma, K. Chatterjee, and T. A. Henzinger, “Compositional
policy learning in stochastic control systems with formal guarantees,” in 37th
Conference on Neural Information Processing Systems, New Orleans, LO, United
States, 2023.
ista: 'Zikelic D, Lechner M, Verma A, Chatterjee K, Henzinger TA. 2023. Compositional
policy learning in stochastic control systems with formal guarantees. 37th Conference
on Neural Information Processing Systems. NeurIPS: Neural Information Processing
Systems.'
mla: Zikelic, Dorde, et al. “Compositional Policy Learning in Stochastic Control
Systems with Formal Guarantees.” 37th Conference on Neural Information Processing
Systems, 2023.
short: D. Zikelic, M. Lechner, A. Verma, K. Chatterjee, T.A. Henzinger, in:, 37th
Conference on Neural Information Processing Systems, 2023.
conference:
end_date: 2023-12-16
location: New Orleans, LO, United States
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2023-12-10
date_created: 2024-02-25T09:23:24Z
date_published: 2023-12-15T00:00:00Z
date_updated: 2025-07-14T09:10:04Z
day: '15'
department:
- _id: ToHe
- _id: KrCh
ec_funded: 1
external_id:
arxiv:
- '2312.01456'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2312.01456
month: '12'
oa: 1
oa_version: Preprint
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
publication: 37th Conference on Neural Information Processing Systems
publication_status: epub_ahead
quality_controlled: '1'
status: public
title: Compositional policy learning in stochastic control systems with formal guarantees
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '13142'
abstract:
- lang: eng
text: Reinforcement learning has received much attention for learning controllers
of deterministic systems. We consider a learner-verifier framework for stochastic
control systems and survey recent methods that formally guarantee a conjunction
of reachability and safety properties. Given a property and a lower bound on the
probability of the property being satisfied, our framework jointly learns a control
policy and a formal certificate to ensure the satisfaction of the property with
a desired probability threshold. Both the control policy and the formal certificate
are continuous functions from states to reals, which are learned as parameterized
neural networks. While in the deterministic case, the certificates are invariant
and barrier functions for safety, or Lyapunov and ranking functions for liveness,
in the stochastic case the certificates are supermartingales. For certificate
verification, we use interval arithmetic abstract interpretation to bound the
expected values of neural network functions.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC
CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. A learner-verifier framework
for neural network controllers and certificates of stochastic systems. In: Tools
and Algorithms for the Construction and Analysis of Systems . Vol 13993. Springer
Nature; 2023:3-25. doi:10.1007/978-3-031-30823-9_1'
apa: 'Chatterjee, K., Henzinger, T. A., Lechner, M., & Zikelic, D. (2023). A
learner-verifier framework for neural network controllers and certificates of
stochastic systems. In Tools and Algorithms for the Construction and Analysis
of Systems (Vol. 13993, pp. 3–25). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-30823-9_1'
chicago: Chatterjee, Krishnendu, Thomas A Henzinger, Mathias Lechner, and Dorde
Zikelic. “A Learner-Verifier Framework for Neural Network Controllers and Certificates
of Stochastic Systems.” In Tools and Algorithms for the Construction and Analysis
of Systems , 13993:3–25. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30823-9_1.
ieee: K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic, “A learner-verifier
framework for neural network controllers and certificates of stochastic systems,”
in Tools and Algorithms for the Construction and Analysis of Systems ,
Paris, France, 2023, vol. 13993, pp. 3–25.
ista: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. 2023. A learner-verifier
framework for neural network controllers and certificates of stochastic systems.
Tools and Algorithms for the Construction and Analysis of Systems . TACAS: Tools
and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13993,
3–25.'
mla: Chatterjee, Krishnendu, et al. “A Learner-Verifier Framework for Neural Network
Controllers and Certificates of Stochastic Systems.” Tools and Algorithms for
the Construction and Analysis of Systems , vol. 13993, Springer Nature, 2023,
pp. 3–25, doi:10.1007/978-3-031-30823-9_1.
short: K. Chatterjee, T.A. Henzinger, M. Lechner, D. Zikelic, in:, Tools and Algorithms
for the Construction and Analysis of Systems , Springer Nature, 2023, pp. 3–25.
conference:
end_date: 2023-04-27
location: Paris, France
name: 'TACAS: Tools and Algorithms for the Construction and Analysis of Systems'
start_date: 2023-04-22
date_created: 2023-06-18T22:00:47Z
date_published: 2023-04-22T00:00:00Z
date_updated: 2025-07-14T09:09:52Z
day: '22'
ddc:
- '000'
department:
- _id: KrCh
- _id: ToHe
doi: 10.1007/978-3-031-30823-9_1
ec_funded: 1
file:
- access_level: open_access
checksum: 3d8a8bb24d211bc83360dfc2fd744307
content_type: application/pdf
creator: dernst
date_created: 2023-06-19T08:29:30Z
date_updated: 2023-06-19T08:29:30Z
file_id: '13150'
file_name: 2023_LNCS_Chatterjee.pdf
file_size: 528455
relation: main_file
success: 1
file_date_updated: 2023-06-19T08:29:30Z
has_accepted_license: '1'
intvolume: ' 13993'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
page: 3-25
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: 'Tools and Algorithms for the Construction and Analysis of Systems '
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031308222'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: A learner-verifier framework for neural network controllers and certificates
of stochastic systems
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: 13993
year: '2023'
...
---
_id: '14242'
abstract:
- lang: eng
text: We study the problem of training and certifying adversarially robust quantized
neural networks (QNNs). Quantization is a technique for making neural networks
more efficient by running them using low-bit integer arithmetic and is therefore
commonly adopted in industry. Recent work has shown that floating-point neural
networks that have been verified to be robust can become vulnerable to adversarial
attacks after quantization, and certification of the quantized representation
is necessary to guarantee robustness. In this work, we present quantization-aware
interval bound propagation (QA-IBP), a novel method for training robust QNNs.
Inspired by advances in robust learning of non-quantized networks, our training
algorithm computes the gradient of an abstract representation of the actual network.
Unlike existing approaches, our method can handle the discrete semantics of QNNs.
Based on QA-IBP, we also develop a complete verification procedure for verifying
the adversarial robustness of QNNs, which is guaranteed to terminate and produce
a correct answer. Compared to existing approaches, the key advantage of our verification
procedure is that it runs entirely on GPU or other accelerator devices. We demonstrate
experimentally that our approach significantly outperforms existing methods and
establish the new state-of-the-art for training and certifying the robustness
of QNNs.
acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093, ERC
CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. Research
was sponsored by the United\r\nStates Air Force Research Laboratory and the United
States Air Force Artificial Intelligence Accelerator and was accomplished under
Cooperative Agreement Number FA8750-19-2-\r\n1000. The views and conclusions contained
in this document are those of the authors and should not be interpreted as representing
the official policies, either expressed or implied,\r\nof the United States Air
Force or the U.S. Government. The U.S. Government is authorized to reproduce and
distribute reprints for Government purposes notwithstanding any copyright\r\nnotation
herein. The research was also funded in part by the AI2050 program at Schmidt Futures
(Grant G-22-63172) and Capgemini SE."
article_processing_charge: No
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
- first_name: Daniela
full_name: Rus, Daniela
last_name: Rus
citation:
ama: 'Lechner M, Zikelic D, Chatterjee K, Henzinger TA, Rus D. Quantization-aware
interval bound propagation for training certifiably robust quantized neural networks.
In: Proceedings of the 37th AAAI Conference on Artificial Intelligence.
Vol 37. Association for the Advancement of Artificial Intelligence; 2023:14964-14973.
doi:10.1609/aaai.v37i12.26747'
apa: 'Lechner, M., Zikelic, D., Chatterjee, K., Henzinger, T. A., & Rus, D.
(2023). Quantization-aware interval bound propagation for training certifiably
robust quantized neural networks. In Proceedings of the 37th AAAI Conference
on Artificial Intelligence (Vol. 37, pp. 14964–14973). Washington, DC, United
States: Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v37i12.26747'
chicago: Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, Thomas A Henzinger,
and Daniela Rus. “Quantization-Aware Interval Bound Propagation for Training Certifiably
Robust Quantized Neural Networks.” In Proceedings of the 37th AAAI Conference
on Artificial Intelligence, 37:14964–73. Association for the Advancement of
Artificial Intelligence, 2023. https://doi.org/10.1609/aaai.v37i12.26747.
ieee: M. Lechner, D. Zikelic, K. Chatterjee, T. A. Henzinger, and D. Rus, “Quantization-aware
interval bound propagation for training certifiably robust quantized neural networks,”
in Proceedings of the 37th AAAI Conference on Artificial Intelligence,
Washington, DC, United States, 2023, vol. 37, no. 12, pp. 14964–14973.
ista: 'Lechner M, Zikelic D, Chatterjee K, Henzinger TA, Rus D. 2023. Quantization-aware
interval bound propagation for training certifiably robust quantized neural networks.
Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI: Conference
on Artificial Intelligence vol. 37, 14964–14973.'
mla: Lechner, Mathias, et al. “Quantization-Aware Interval Bound Propagation for
Training Certifiably Robust Quantized Neural Networks.” Proceedings of the
37th AAAI Conference on Artificial Intelligence, vol. 37, no. 12, Association
for the Advancement of Artificial Intelligence, 2023, pp. 14964–73, doi:10.1609/aaai.v37i12.26747.
short: M. Lechner, D. Zikelic, K. Chatterjee, T.A. Henzinger, D. Rus, in:, Proceedings
of the 37th AAAI Conference on Artificial Intelligence, Association for the Advancement
of Artificial Intelligence, 2023, pp. 14964–14973.
conference:
end_date: 2023-02-14
location: Washington, DC, United States
name: 'AAAI: Conference on Artificial Intelligence'
start_date: 2023-02-07
date_created: 2023-08-27T22:01:17Z
date_published: 2023-06-26T00:00:00Z
date_updated: 2025-07-14T09:09:56Z
day: '26'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v37i12.26747
ec_funded: 1
external_id:
arxiv:
- '2211.16187'
intvolume: ' 37'
issue: '12'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2211.16187
month: '06'
oa: 1
oa_version: Preprint
page: 14964-14973
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Proceedings of the 37th AAAI Conference on Artificial Intelligence
publication_identifier:
isbn:
- '9781577358800'
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
scopus_import: '1'
status: public
title: Quantization-aware interval bound propagation for training certifiably robust
quantized neural networks
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2023'
...
---
_id: '14243'
abstract:
- lang: eng
text: 'Two-player zero-sum "graph games" are central in logic, verification, and
multi-agent systems. The game proceeds by placing a token on a vertex of a graph,
and allowing the players to move it to produce an infinite path, which determines
the winner or payoff of the game. Traditionally, the players alternate turns in
moving the token. In "bidding games", however, the players have budgets and in
each turn, an auction (bidding) determines which player moves the token. So far,
bidding games have only been studied as full-information games. In this work we
initiate the study of partial-information bidding games: we study bidding games
in which a player''s initial budget is drawn from a known probability distribution.
We show that while for some bidding mechanisms and objectives, it is straightforward
to adapt the results from the full-information setting to the partial-information
setting, for others, the analysis is significantly more challenging, requires
new techniques, and gives rise to interesting results. Specifically, we study
games with "mean-payoff" objectives in combination with "poorman" bidding. We
construct optimal strategies for a partially-informed player who plays against
a fully-informed adversary. We show that, somewhat surprisingly, the "value" under
pure strategies does not necessarily exist in such games.'
acknowledgement: This research was supported in part by ISF grant no.1679/21, by the
ERC CoG 863818 (ForM-SMArt), and the European Union’s Horizon 2020 research and
innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
article_processing_charge: No
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: Proceedings of the 37th AAAI Conference on Artificial Intelligence.
Vol 37. ; 2023:5464-5471. doi:10.1609/aaai.v37i5.25679'
apa: Avni, G., Jecker, I. R., & Zikelic, D. (2023). Bidding graph games with
partially-observable budgets. In Proceedings of the 37th AAAI Conference on
Artificial Intelligence (Vol. 37, pp. 5464–5471). Washington, DC, United States.
https://doi.org/10.1609/aaai.v37i5.25679
chicago: Avni, Guy, Ismael R Jecker, and Dorde Zikelic. “Bidding Graph Games with
Partially-Observable Budgets.” In Proceedings of the 37th AAAI Conference on
Artificial Intelligence, 37:5464–71, 2023. https://doi.org/10.1609/aaai.v37i5.25679.
ieee: G. Avni, I. R. Jecker, and D. Zikelic, “Bidding graph games with partially-observable
budgets,” in Proceedings of the 37th AAAI Conference on Artificial Intelligence,
Washington, DC, United States, 2023, vol. 37, no. 5, pp. 5464–5471.
ista: 'Avni G, Jecker IR, Zikelic D. 2023. Bidding graph games with partially-observable
budgets. Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI:
Conference on Artificial Intelligence vol. 37, 5464–5471.'
mla: Avni, Guy, et al. “Bidding Graph Games with Partially-Observable Budgets.”
Proceedings of the 37th AAAI Conference on Artificial Intelligence, vol.
37, no. 5, 2023, pp. 5464–71, doi:10.1609/aaai.v37i5.25679.
short: G. Avni, I.R. Jecker, D. Zikelic, in:, Proceedings of the 37th AAAI Conference
on Artificial Intelligence, 2023, pp. 5464–5471.
conference:
end_date: 2023-02-14
location: Washington, DC, United States
name: 'AAAI: Conference on Artificial Intelligence'
start_date: 2023-02-07
date_created: 2023-08-27T22:01:18Z
date_published: 2023-06-27T00:00:00Z
date_updated: 2025-07-14T09:09:56Z
day: '27'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v37i5.25679
ec_funded: 1
external_id:
arxiv:
- '2211.13626'
intvolume: ' 37'
issue: '5'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1609/aaai.v37i5.25679
month: '06'
oa: 1
oa_version: Published Version
page: 5464-5471
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Proceedings of the 37th AAAI Conference on Artificial Intelligence
publication_identifier:
isbn:
- '9781577358800'
publication_status: published
quality_controlled: '1'
scopus_import: '1'
status: public
title: Bidding graph games with partially-observable budgets
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2023'
...
---
_id: '11459'
abstract:
- lang: eng
text: 'We present a novel approach to differential cost analysis that, given a program
revision, attempts to statically bound the difference in resource usage, or cost,
between the two program versions. Differential cost analysis is particularly interesting
because of the many compelling applications for it, such as detecting resource-use
regressions at code-review time or proving the absence of certain side-channel
vulnerabilities. One prior approach to differential cost analysis is to apply
relational reasoning that conceptually constructs a product program on which one
can over-approximate the difference in costs between the two program versions.
However, a significant challenge in any relational approach is effectively aligning
the program versions to get precise results. In this paper, our key insight is
that we can avoid the need for and the limitations of program alignment if, instead,
we bound the difference of two cost-bound summaries rather than directly bounding
the concrete cost difference. In particular, our method computes a threshold value
for the maximal difference in cost between two program versions simultaneously
using two kinds of cost-bound summaries---a potential function that evaluates
to an upper bound for the cost incurred in the first program and an anti-potential
function that evaluates to a lower bound for the cost incurred in the second.
Our method has a number of desirable properties: it can be fully automated, it
allows optimizing the threshold value on relative cost, it is suitable for programs
that are not syntactically similar, and it supports non-determinism. We have evaluated
an implementation of our approach on a number of program pairs collected from
the literature, and we find that our method computes tight threshold values on
relative cost in most examples.'
acknowledgement: "We thank Shaun Willows, Thomas Lugnet, and the Living Room Application
Vending team for suggesting threshold\r\nbounds as a developer-friendly way to interact
with a differential cost analyzer, and we thank Jim Christy, Daniel\r\nSchoepe,
and the Prime Video Automated Reasoning team for their support and helpful suggestions
throughout the\r\nproject. We also thank Michael Emmi for feedback on an earlier
version of this paper. And finally, we thank the anonymous reviewers for their useful
feedback and Aws Albarghouthi for shepherding the final version of the paper. Ðorđe
Žikelić was also partially supported by ERC CoG 863818 (FoRM-SMArt)."
article_processing_charge: No
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: Bor-Yuh Evan
full_name: Chang, Bor-Yuh Evan
last_name: Chang
- first_name: Pauline
full_name: Bolignano, Pauline
last_name: Bolignano
- first_name: Franco
full_name: Raimondi, Franco
last_name: Raimondi
citation:
ama: 'Zikelic D, Chang B-YE, Bolignano P, Raimondi F. Differential cost analysis
with simultaneous potentials and anti-potentials. In: Proceedings of the 43rd
ACM SIGPLAN International Conference on Programming Language Design and Implementation.
Association for Computing Machinery; 2022:442-457. doi:10.1145/3519939.3523435'
apa: 'Zikelic, D., Chang, B.-Y. E., Bolignano, P., & Raimondi, F. (2022). Differential
cost analysis with simultaneous potentials and anti-potentials. In Proceedings
of the 43rd ACM SIGPLAN International Conference on Programming Language Design
and Implementation (pp. 442–457). San Diego, CA, United States: Association
for Computing Machinery. https://doi.org/10.1145/3519939.3523435'
chicago: Zikelic, Dorde, Bor-Yuh Evan Chang, Pauline Bolignano, and Franco Raimondi.
“Differential Cost Analysis with Simultaneous Potentials and Anti-Potentials.”
In Proceedings of the 43rd ACM SIGPLAN International Conference on Programming
Language Design and Implementation, 442–57. Association for Computing Machinery,
2022. https://doi.org/10.1145/3519939.3523435.
ieee: D. Zikelic, B.-Y. E. Chang, P. Bolignano, and F. Raimondi, “Differential cost
analysis with simultaneous potentials and anti-potentials,” in Proceedings
of the 43rd ACM SIGPLAN International Conference on Programming Language Design
and Implementation, San Diego, CA, United States, 2022, pp. 442–457.
ista: 'Zikelic D, Chang B-YE, Bolignano P, Raimondi F. 2022. Differential cost analysis
with simultaneous potentials and anti-potentials. Proceedings of the 43rd ACM
SIGPLAN International Conference on Programming Language Design and Implementation.
PLDI: Programming Language Design and Implementation, 442–457.'
mla: Zikelic, Dorde, et al. “Differential Cost Analysis with Simultaneous Potentials
and Anti-Potentials.” Proceedings of the 43rd ACM SIGPLAN International Conference
on Programming Language Design and Implementation, Association for Computing
Machinery, 2022, pp. 442–57, doi:10.1145/3519939.3523435.
short: D. Zikelic, B.-Y.E. Chang, P. Bolignano, F. Raimondi, in:, Proceedings of
the 43rd ACM SIGPLAN International Conference on Programming Language Design and
Implementation, Association for Computing Machinery, 2022, pp. 442–457.
conference:
end_date: 2022-06-17
location: San Diego, CA, United States
name: 'PLDI: Programming Language Design and Implementation'
start_date: 2022-06-13
date_created: 2022-06-21T09:26:15Z
date_published: 2022-06-09T00:00:00Z
date_updated: 2025-07-14T09:09:54Z
day: '09'
ddc:
- '000'
department:
- _id: GradSch
- _id: KrCh
doi: 10.1145/3519939.3523435
ec_funded: 1
external_id:
arxiv:
- '2204.00870'
isi:
- '000850435600030'
file:
- access_level: open_access
checksum: 7eb915a2ca5b5ce4729321f33b2e16e1
content_type: application/pdf
creator: dernst
date_created: 2022-06-27T07:38:21Z
date_updated: 2022-06-27T07:38:21Z
file_id: '11466'
file_name: 2022_PLDI_Zikelic.pdf
file_size: 318697
relation: main_file
success: 1
file_date_updated: 2022-06-27T07:38:21Z
has_accepted_license: '1'
isi: 1
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
month: '06'
oa: 1
oa_version: Published Version
page: 442-457
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Proceedings of the 43rd ACM SIGPLAN International Conference on Programming
Language Design and Implementation
publication_identifier:
isbn:
- '9781450392655'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
scopus_import: '1'
status: public
title: Differential cost analysis with simultaneous potentials and anti-potentials
tmp:
image: /images/cc_by_nc_nd.png
legal_code_url: https://creativecommons.org/licenses/by-nc-nd/4.0/legalcode
name: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
(CC BY-NC-ND 4.0)
short: CC BY-NC-ND (4.0)
type: conference
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
year: '2022'
...
---
_id: '14600'
abstract:
- lang: eng
text: We study the problem of learning controllers for discrete-time non-linear
stochastic dynamical systems with formal reach-avoid guarantees. This work presents
the first method for providing formal reach-avoid guarantees, which combine and
generalize stability and safety guarantees, with a tolerable probability threshold
$p\in[0,1]$ over the infinite time horizon. Our method leverages advances in machine
learning literature and it represents formal certificates as neural networks.
In particular, we learn a certificate in the form of a reach-avoid supermartingale
(RASM), a novel notion that we introduce in this work. Our RASMs provide reachability
and avoidance guarantees by imposing constraints on what can be viewed as a stochastic
extension of level sets of Lyapunov functions for deterministic systems. Our approach
solves several important problems -- it can be used to learn a control policy
from scratch, to verify a reach-avoid specification for a fixed control policy,
or to fine-tune a pre-trained policy if it does not satisfy the reach-avoid specification.
We validate our approach on $3$ stochastic non-linear reinforcement learning tasks.
article_processing_charge: No
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. arXiv. doi:10.48550/ARXIV.2210.05308
apa: Zikelic, D., Lechner, M., Henzinger, T. A., & Chatterjee, K. (n.d.). Learning
control policies for stochastic systems with reach-avoid guarantees. arXiv.
https://doi.org/10.48550/ARXIV.2210.05308
chicago: Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee.
“Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.”
ArXiv, n.d. https://doi.org/10.48550/ARXIV.2210.05308.
ieee: D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control
policies for stochastic systems with reach-avoid guarantees,” arXiv. .
ista: Zikelic D, Lechner M, Henzinger TA, Chatterjee K. Learning control policies
for stochastic systems with reach-avoid guarantees. arXiv, 10.48550/ARXIV.2210.05308.
mla: Zikelic, Dorde, et al. “Learning Control Policies for Stochastic Systems with
Reach-Avoid Guarantees.” ArXiv, doi:10.48550/ARXIV.2210.05308.
short: D. Zikelic, M. Lechner, T.A. Henzinger, K. Chatterjee, ArXiv (n.d.).
date_created: 2023-11-24T13:10:09Z
date_published: 2022-11-29T00:00:00Z
date_updated: 2025-07-14T09:10:02Z
day: '29'
department:
- _id: KrCh
- _id: ToHe
doi: 10.48550/ARXIV.2210.05308
ec_funded: 1
external_id:
arxiv:
- '2210.05308'
language:
- iso: eng
license: https://creativecommons.org/licenses/by-sa/4.0/
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2210.05308
month: '11'
oa: 1
oa_version: Preprint
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: arXiv
publication_status: submitted
related_material:
record:
- id: '14539'
relation: dissertation_contains
status: public
- id: '14830'
relation: later_version
status: public
status: public
title: Learning control policies for stochastic systems with reach-avoid guarantees
tmp:
image: /images/cc_by_sa.png
legal_code_url: https://creativecommons.org/licenses/by-sa/4.0/legalcode
name: Creative Commons Attribution-ShareAlike 4.0 International Public License (CC
BY-SA 4.0)
short: CC BY-SA (4.0)
type: preprint
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2022'
...
---
_id: '14601'
abstract:
- lang: eng
text: "In this work, we address the problem of learning provably stable neural\r\nnetwork
policies for stochastic control systems. While recent work has\r\ndemonstrated
the feasibility of certifying given policies using martingale\r\ntheory, the problem
of how to learn such policies is little explored. Here, we\r\nstudy the effectiveness
of jointly learning a policy together with a martingale\r\ncertificate that proves
its stability using a single learning algorithm. We\r\nobserve that the joint
optimization problem becomes easily stuck in local\r\nminima when starting from
a randomly initialized policy. Our results suggest\r\nthat some form of pre-training
of the policy is required for the joint\r\noptimization to repair and verify the
policy successfully."
article_processing_charge: No
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: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: Zikelic D, Lechner M, Chatterjee K, Henzinger TA. Learning stabilizing policies
in stochastic control systems. arXiv. doi:10.48550/arXiv.2205.11991
apa: Zikelic, D., Lechner, M., Chatterjee, K., & Henzinger, T. A. (n.d.). Learning
stabilizing policies in stochastic control systems. arXiv. https://doi.org/10.48550/arXiv.2205.11991
chicago: Zikelic, Dorde, Mathias Lechner, Krishnendu Chatterjee, and Thomas A Henzinger.
“Learning Stabilizing Policies in Stochastic Control Systems.” ArXiv, n.d.
https://doi.org/10.48550/arXiv.2205.11991.
ieee: D. Zikelic, M. Lechner, K. Chatterjee, and T. A. Henzinger, “Learning stabilizing
policies in stochastic control systems,” arXiv. .
ista: Zikelic D, Lechner M, Chatterjee K, Henzinger TA. Learning stabilizing policies
in stochastic control systems. arXiv, 10.48550/arXiv.2205.11991.
mla: Zikelic, Dorde, et al. “Learning Stabilizing Policies in Stochastic Control
Systems.” ArXiv, doi:10.48550/arXiv.2205.11991.
short: D. Zikelic, M. Lechner, K. Chatterjee, T.A. Henzinger, ArXiv (n.d.).
date_created: 2023-11-24T13:22:30Z
date_published: 2022-05-24T00:00:00Z
date_updated: 2025-07-14T09:10:00Z
day: '24'
department:
- _id: KrCh
- _id: ToHe
doi: 10.48550/arXiv.2205.11991
ec_funded: 1
external_id:
arxiv:
- '2205.11991'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2205.11991
month: '05'
oa: 1
oa_version: Preprint
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: arXiv
publication_status: submitted
related_material:
record:
- id: '14539'
relation: dissertation_contains
status: public
status: public
title: Learning stabilizing policies in stochastic control systems
type: preprint
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2022'
...
---
_id: '12000'
abstract:
- lang: eng
text: "We consider the quantitative problem of obtaining lower-bounds on the probability
of termination of a given non-deterministic probabilistic program. Specifically,
given a non-termination threshold p∈[0,1], we aim for certificates proving that
the program terminates with probability at least 1−p. The basic idea of our approach
is to find a terminating stochastic invariant, i.e. a subset SI of program states
such that (i) the probability of the program ever leaving SI is no more than p,
and (ii) almost-surely, the program either leaves SI or terminates.\r\n\r\nWhile
stochastic invariants are already well-known, we provide the first proof that
the idea above is not only sound, but also complete for quantitative termination
analysis. We then introduce a novel sound and complete characterization of stochastic
invariants that enables template-based approaches for easy synthesis of quantitative
termination certificates, especially in affine or polynomial forms. Finally, by
combining this idea with the existing martingale-based methods that are relatively
complete for qualitative termination analysis, we obtain the first automated,
sound, and relatively complete algorithm for quantitative termination analysis.
Notably, our completeness guarantees for quantitative termination analysis are
as strong as the best-known methods for the qualitative variant.\r\n\r\nOur prototype
implementation demonstrates the effectiveness of our approach on various probabilistic
programs. We also demonstrate that our algorithm certifies lower bounds on termination
probability for probabilistic programs that are beyond the reach of previous methods."
acknowledgement: This research was partially supported by the ERC CoG 863818 (ForM-SMArt),
the HKUST-Kaisa Joint Research Institute Project Grant HKJRI3A-055, the HKUST Startup
Grant R9272 and the European Union’s Horizon 2020 research and innovation programme
under the Marie Skłodowska-Curie Grant Agreement No. 665385.
alternative_title:
- LNCS
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Amir Kafshdar
full_name: Goharshady, Amir Kafshdar
id: 391365CE-F248-11E8-B48F-1D18A9856A87
last_name: Goharshady
orcid: 0000-0003-1702-6584
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Chatterjee K, Goharshady AK, Meggendorfer T, Zikelic D. Sound and complete
certificates for auantitative termination analysis of probabilistic programs.
In: Proceedings of the 34th International Conference on Computer Aided Verification.
Vol 13371. Springer; 2022:55-78. doi:10.1007/978-3-031-13185-1_4'
apa: 'Chatterjee, K., Goharshady, A. K., Meggendorfer, T., & Zikelic, D. (2022).
Sound and complete certificates for auantitative termination analysis of probabilistic
programs. In Proceedings of the 34th International Conference on Computer Aided
Verification (Vol. 13371, pp. 55–78). Haifa, Israel: Springer. https://doi.org/10.1007/978-3-031-13185-1_4'
chicago: Chatterjee, Krishnendu, Amir Kafshdar Goharshady, Tobias Meggendorfer,
and Dorde Zikelic. “Sound and Complete Certificates for Auantitative Termination
Analysis of Probabilistic Programs.” In Proceedings of the 34th International
Conference on Computer Aided Verification, 13371:55–78. Springer, 2022. https://doi.org/10.1007/978-3-031-13185-1_4.
ieee: K. Chatterjee, A. K. Goharshady, T. Meggendorfer, and D. Zikelic, “Sound and complete
certificates for auantitative termination analysis of probabilistic programs,”
in Proceedings of the 34th International Conference on Computer Aided Verification,
Haifa, Israel, 2022, vol. 13371, pp. 55–78.
ista: 'Chatterjee K, Goharshady AK, Meggendorfer T, Zikelic D. 2022. Sound and complete
certificates for auantitative termination analysis of probabilistic programs.
Proceedings of the 34th International Conference on Computer Aided Verification.
CAV: Computer Aided Verification, LNCS, vol. 13371, 55–78.'
mla: Chatterjee, Krishnendu, et al. “Sound and Complete Certificates for Auantitative
Termination Analysis of Probabilistic Programs.” Proceedings of the 34th International
Conference on Computer Aided Verification, vol. 13371, Springer, 2022, pp.
55–78, doi:10.1007/978-3-031-13185-1_4.
short: K. Chatterjee, A.K. Goharshady, T. Meggendorfer, D. Zikelic, in:, Proceedings
of the 34th International Conference on Computer Aided Verification, Springer,
2022, pp. 55–78.
conference:
end_date: 2022-08-10
location: Haifa, Israel
name: 'CAV: Computer Aided Verification'
start_date: 2022-08-07
date_created: 2022-08-28T22:02:02Z
date_published: 2022-08-07T00:00:00Z
date_updated: 2025-07-14T09:09:58Z
day: '07'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/978-3-031-13185-1_4
ec_funded: 1
external_id:
isi:
- '000870304500004'
file:
- access_level: open_access
checksum: 24e0f810ec52735a90ade95198bc641d
content_type: application/pdf
creator: alisjak
date_created: 2022-08-29T09:17:01Z
date_updated: 2022-08-29T09:17:01Z
file_id: '12003'
file_name: 2022_LNCS_Chatterjee.pdf
file_size: 505094
relation: main_file
success: 1
file_date_updated: 2022-08-29T09:17:01Z
has_accepted_license: '1'
intvolume: ' 13371'
isi: 1
language:
- iso: eng
month: '08'
oa: 1
oa_version: Published Version
page: 55-78
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Proceedings of the 34th International Conference on Computer Aided Verification
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031131844'
issn:
- 0302-9743
publication_status: published
publisher: Springer
quality_controlled: '1'
related_material:
record:
- id: '14539'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Sound and complete certificates for auantitative termination analysis of probabilistic
programs
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 13371
year: '2022'
...
---
_id: '12102'
abstract:
- lang: eng
text: 'Given a Markov chain M = (V, v_0, δ), with state space V and a starting state
v_0, and a probability threshold ε, an ε-core is a subset C of states that is
left with probability at most ε. More formally, C ⊆ V is an ε-core, iff ℙ[reach
(V\C)] ≤ ε. Cores have been applied in a wide variety of verification problems
over Markov chains, Markov decision processes, and probabilistic programs, as
a means of discarding uninteresting and low-probability parts of a probabilistic
system and instead being able to focus on the states that are likely to be encountered
in a real-world run. In this work, we focus on the problem of computing a minimal
ε-core in a Markov chain. Our contributions include both negative and positive
results: (i) We show that the decision problem on the existence of an ε-core of
a given size is NP-complete. This solves an open problem posed in [Jan Kretínský
and Tobias Meggendorfer, 2020]. We additionally show that the problem remains
NP-complete even when limited to acyclic Markov chains with bounded maximal vertex
degree; (ii) We provide a polynomial time algorithm for computing a minimal ε-core
on Markov chains over control-flow graphs of structured programs. A straightforward
combination of our algorithm with standard branch prediction techniques allows
one to apply the idea of cores to find a subset of program lines that are left
with low probability and then focus any desired static analysis on this core subset.'
acknowledgement: "The research was partially supported by the Hong Kong Research Grants
Council ECS\r\nProject No. 26208122, ERC CoG 863818 (FoRM-SMArt), the European Union’s
Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie
Grant Agreement No. 665385, HKUST– Kaisa Joint Research Institute Project Grant
HKJRI3A-055 and HKUST Startup Grant R9272. Ali Ahmadi and Roodabeh Safavi were interns
at HKUST."
article_number: '29'
article_processing_charge: No
author:
- first_name: Ali
full_name: Ahmadi, Ali
last_name: Ahmadi
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Amir Kafshdar
full_name: Goharshady, Amir Kafshdar
id: 391365CE-F248-11E8-B48F-1D18A9856A87
last_name: Goharshady
orcid: 0000-0003-1702-6584
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
- first_name: Roodabeh
full_name: Safavi Hemami, Roodabeh
id: 72ed2640-8972-11ed-ae7b-f9c81ec75154
last_name: Safavi Hemami
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Ahmadi A, Chatterjee K, Goharshady AK, Meggendorfer T, Safavi Hemami R, Zikelic
D. Algorithms and hardness results for computing cores of Markov chains. In: 42nd
IARCS Annual Conference on Foundations of Software Technology and Theoretical
Computer Science. Vol 250. Schloss Dagstuhl - Leibniz-Zentrum für Informatik;
2022. doi:10.4230/LIPIcs.FSTTCS.2022.29'
apa: 'Ahmadi, A., Chatterjee, K., Goharshady, A. K., Meggendorfer, T., Safavi Hemami,
R., & Zikelic, D. (2022). Algorithms and hardness results for computing cores
of Markov chains. In 42nd IARCS Annual Conference on Foundations of Software
Technology and Theoretical Computer Science (Vol. 250). Madras, India: Schloss
Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.FSTTCS.2022.29'
chicago: Ahmadi, Ali, Krishnendu Chatterjee, Amir Kafshdar Goharshady, Tobias Meggendorfer,
Roodabeh Safavi Hemami, and Dorde Zikelic. “Algorithms and Hardness Results for
Computing Cores of Markov Chains.” In 42nd IARCS Annual Conference on Foundations
of Software Technology and Theoretical Computer Science, Vol. 250. Schloss
Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.FSTTCS.2022.29.
ieee: A. Ahmadi, K. Chatterjee, A. K. Goharshady, T. Meggendorfer, R. Safavi Hemami,
and D. Zikelic, “Algorithms and hardness results for computing cores of Markov
chains,” in 42nd IARCS Annual Conference on Foundations of Software Technology
and Theoretical Computer Science, Madras, India, 2022, vol. 250.
ista: 'Ahmadi A, Chatterjee K, Goharshady AK, Meggendorfer T, Safavi Hemami R, Zikelic
D. 2022. Algorithms and hardness results for computing cores of Markov chains.
42nd IARCS Annual Conference on Foundations of Software Technology and Theoretical
Computer Science. FSTTC: Foundations of Software Technology and Theoretical Computer
Science vol. 250, 29.'
mla: Ahmadi, Ali, et al. “Algorithms and Hardness Results for Computing Cores of
Markov Chains.” 42nd IARCS Annual Conference on Foundations of Software Technology
and Theoretical Computer Science, vol. 250, 29, Schloss Dagstuhl - Leibniz-Zentrum
für Informatik, 2022, doi:10.4230/LIPIcs.FSTTCS.2022.29.
short: A. Ahmadi, K. Chatterjee, A.K. Goharshady, T. Meggendorfer, R. Safavi Hemami,
D. Zikelic, in:, 42nd IARCS Annual Conference on Foundations of Software Technology
and Theoretical Computer Science, Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
2022.
conference:
end_date: 2022-12-20
location: Madras, India
name: 'FSTTC: Foundations of Software Technology and Theoretical Computer Science'
start_date: 2022-12-18
date_created: 2023-01-01T23:00:50Z
date_published: 2022-12-14T00:00:00Z
date_updated: 2025-07-14T09:09:55Z
day: '14'
ddc:
- '000'
department:
- _id: KrCh
- _id: GradSch
doi: 10.4230/LIPIcs.FSTTCS.2022.29
ec_funded: 1
file:
- access_level: open_access
checksum: 6660c802489013f034c9e8bd57f4d46e
content_type: application/pdf
creator: dernst
date_created: 2023-01-20T10:39:44Z
date_updated: 2023-01-20T10:39:44Z
file_id: '12324'
file_name: 2022_LIPICs_Ahmadi.pdf
file_size: 872534
relation: main_file
success: 1
file_date_updated: 2023-01-20T10:39:44Z
has_accepted_license: '1'
intvolume: ' 250'
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: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: 42nd IARCS Annual Conference on Foundations of Software Technology and
Theoretical Computer Science
publication_identifier:
isbn:
- '9783959772617'
issn:
- 1868-8969
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
status: public
title: Algorithms and hardness results for computing cores of Markov chains
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: 250
year: '2022'
...
---
_id: '12257'
abstract:
- lang: eng
text: Structural balance theory is an established framework for studying social
relationships of friendship and enmity. These relationships are modeled by a signed
network whose energy potential measures the level of imbalance, while stochastic
dynamics drives the network toward a state of minimum energy that captures social
balance. It is known that this energy landscape has local minima that can trap
socially aware dynamics, preventing it from reaching balance. Here we first study
the robustness and attractor properties of these local minima. We show that a
stochastic process can reach them from an abundance of initial states and that
some local minima cannot be escaped by mild perturbations of the network. Motivated
by these anomalies, we introduce best-edge dynamics (BED), a new plausible stochastic
process. We prove that BED always reaches balance and that it does so fast in
various interesting settings.
acknowledgement: "K.C. acknowledges support from ERC Start Grant No. (279307: Graph
Games), ERC Consolidator Grant No. (863818: ForM-SMart), and Austrian Science Fund
(FWF)\r\nGrants No. P23499-N23 and No. S11407-N23 (RiSE). This project has received
funding from the European Union’s Horizon 2020 research and innovation programme
under the Marie\r\nSkłodowska-Curie Grant Agreement No. 665385."
article_number: '034321'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Jakub
full_name: Svoboda, Jakub
id: 130759D2-D7DD-11E9-87D2-DE0DE6697425
last_name: Svoboda
orcid: 0000-0002-1419-3267
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
- first_name: Andreas
full_name: Pavlogiannis, Andreas
id: 49704004-F248-11E8-B48F-1D18A9856A87
last_name: Pavlogiannis
orcid: 0000-0002-8943-0722
- first_name: Josef
full_name: Tkadlec, Josef
id: 3F24CCC8-F248-11E8-B48F-1D18A9856A87
last_name: Tkadlec
orcid: 0000-0002-1097-9684
citation:
ama: 'Chatterjee K, Svoboda J, Zikelic D, Pavlogiannis A, Tkadlec J. Social balance
on networks: Local minima and best-edge dynamics. Physical Review E. 2022;106(3).
doi:10.1103/physreve.106.034321'
apa: 'Chatterjee, K., Svoboda, J., Zikelic, D., Pavlogiannis, A., & Tkadlec,
J. (2022). Social balance on networks: Local minima and best-edge dynamics. Physical
Review E. American Physical Society. https://doi.org/10.1103/physreve.106.034321'
chicago: 'Chatterjee, Krishnendu, Jakub Svoboda, Dorde Zikelic, Andreas Pavlogiannis,
and Josef Tkadlec. “Social Balance on Networks: Local Minima and Best-Edge Dynamics.”
Physical Review E. American Physical Society, 2022. https://doi.org/10.1103/physreve.106.034321.'
ieee: 'K. Chatterjee, J. Svoboda, D. Zikelic, A. Pavlogiannis, and J. Tkadlec, “Social
balance on networks: Local minima and best-edge dynamics,” Physical Review
E, vol. 106, no. 3. American Physical Society, 2022.'
ista: 'Chatterjee K, Svoboda J, Zikelic D, Pavlogiannis A, Tkadlec J. 2022. Social
balance on networks: Local minima and best-edge dynamics. Physical Review E. 106(3),
034321.'
mla: 'Chatterjee, Krishnendu, et al. “Social Balance on Networks: Local Minima and
Best-Edge Dynamics.” Physical Review E, vol. 106, no. 3, 034321, American
Physical Society, 2022, doi:10.1103/physreve.106.034321.'
short: K. Chatterjee, J. Svoboda, D. Zikelic, A. Pavlogiannis, J. Tkadlec, Physical
Review E 106 (2022).
date_created: 2023-01-16T09:57:57Z
date_published: 2022-09-29T00:00:00Z
date_updated: 2025-07-14T09:09:49Z
day: '29'
department:
- _id: KrCh
doi: 10.1103/physreve.106.034321
ec_funded: 1
external_id:
arxiv:
- '2210.02394'
isi:
- '000870243100001'
intvolume: ' 106'
isi: 1
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2210.02394
month: '09'
oa: 1
oa_version: Preprint
project:
- _id: 2581B60A-B435-11E9-9278-68D0E5697425
call_identifier: FP7
grant_number: '279307'
name: 'Quantitative Graph Games: Theory and Applications'
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2584A770-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: P 23499-N23
name: Modern Graph Algorithmic Techniques in Formal Verification
- _id: 25863FF4-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11407
name: Game Theory
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Physical Review E
publication_identifier:
eissn:
- 2470-0053
issn:
- 2470-0045
publication_status: published
publisher: American Physical Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'Social balance on networks: Local minima and best-edge dynamics'
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 106
year: '2022'
...
---
_id: '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. Proceedings
of the AAAI Conference on Artificial Intelligence. 2022;36(7):7326-7336. doi:10.1609/aaai.v36i7.20695
apa: Lechner, M., Zikelic, D., Chatterjee, K., & Henzinger, T. A. (2022). Stability
verification in stochastic control systems via neural network supermartingales.
Proceedings of the AAAI Conference on Artificial Intelligence. Association
for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v36i7.20695
chicago: Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, and Thomas A Henzinger.
“Stability Verification in Stochastic Control Systems via Neural Network Supermartingales.”
Proceedings of the AAAI Conference on Artificial Intelligence. Association
for the Advancement of Artificial Intelligence, 2022. https://doi.org/10.1609/aaai.v36i7.20695.
ieee: M. Lechner, D. Zikelic, K. Chatterjee, and T. A. Henzinger, “Stability verification
in stochastic control systems via neural network supermartingales,” Proceedings
of the AAAI Conference on Artificial Intelligence, vol. 36, no. 7. Association
for the Advancement of Artificial Intelligence, pp. 7326–7336, 2022.
ista: Lechner M, Zikelic D, Chatterjee K, Henzinger TA. 2022. Stability verification
in stochastic control systems via neural network supermartingales. Proceedings
of the AAAI Conference on Artificial Intelligence. 36(7), 7326–7336.
mla: Lechner, Mathias, et al. “Stability Verification in Stochastic Control Systems
via Neural Network Supermartingales.” Proceedings of the AAAI Conference on
Artificial Intelligence, vol. 36, no. 7, Association for the Advancement of
Artificial Intelligence, 2022, pp. 7326–36, doi:10.1609/aaai.v36i7.20695.
short: M. Lechner, D. Zikelic, K. Chatterjee, T.A. Henzinger, Proceedings of the
AAAI Conference on Artificial Intelligence 36 (2022) 7326–7336.
date_created: 2023-02-05T17:29:50Z
date_published: 2022-06-28T00:00:00Z
date_updated: 2025-07-14T09:09:58Z
day: '28'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v36i7.20695
ec_funded: 1
external_id:
arxiv:
- '2112.09495'
intvolume: ' 36'
issue: '7'
keyword:
- General Medicine
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2112.09495
month: '06'
oa: 1
oa_version: Preprint
page: 7326-7336
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Proceedings of the AAAI Conference on Artificial Intelligence
publication_identifier:
eissn:
- 2374-3468
isbn:
- '9781577358350'
issn:
- 2159-5399
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
related_material:
record:
- id: '14539'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Stability verification in stochastic control systems via neural network supermartingales
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 36
year: '2022'
...
---
_id: '10665'
abstract:
- lang: eng
text: "Formal verification of neural networks is an active topic of research, and
recent advances have significantly increased the size of the networks that verification
tools can handle. However, most methods are designed for verification of an idealized
model of the actual network which works over real arithmetic and ignores rounding
imprecisions. This idealization is in stark contrast to network quantization,
which is a technique that trades numerical precision for computational efficiency
and is, therefore, often applied in practice. Neglecting rounding errors of such
low-bit quantized neural networks has been shown to lead to wrong conclusions
about the network’s correctness. Thus, the desired approach for verifying quantized
neural networks would be one that takes these rounding errors\r\ninto account.
In this paper, we show that verifying the bitexact implementation of quantized
neural networks with bitvector specifications is PSPACE-hard, even though verifying
idealized real-valued networks and satisfiability of bit-vector specifications
alone are each in NP. Furthermore, we explore several practical heuristics toward
closing the complexity gap between idealized and bit-exact verification. In particular,
we propose three techniques for making SMT-based verification of quantized neural
networks more scalable. Our experiments demonstrate that our proposed methods
allow a speedup of up to three orders of magnitude over existing approaches."
acknowledgement: "This research was supported in part by the Austrian Science Fund
(FWF) under grant Z211-N23 (Wittgenstein\r\nAward), ERC CoG 863818 (FoRM-SMArt),
and the European Union’s Horizon 2020 research and innovation programme under the
Marie Skłodowska-Curie Grant Agreement No. 665385.\r\n"
alternative_title:
- Technical Tracks
article_processing_charge: No
arxiv: 1
author:
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Henzinger TA, Lechner M, Zikelic D. Scalable verification of quantized neural
networks. In: Proceedings of the AAAI Conference on Artificial Intelligence.
Vol 35. AAAI Press; 2021:3787-3795.'
apa: 'Henzinger, T. A., Lechner, M., & Zikelic, D. (2021). Scalable verification
of quantized neural networks. In Proceedings of the AAAI Conference on Artificial
Intelligence (Vol. 35, pp. 3787–3795). Virtual: AAAI Press.'
chicago: Henzinger, Thomas A, Mathias Lechner, and Dorde Zikelic. “Scalable Verification
of Quantized Neural Networks.” In Proceedings of the AAAI Conference on Artificial
Intelligence, 35:3787–95. AAAI Press, 2021.
ieee: T. A. Henzinger, M. Lechner, and D. Zikelic, “Scalable verification of quantized
neural networks,” in Proceedings of the AAAI Conference on Artificial Intelligence,
Virtual, 2021, vol. 35, no. 5A, pp. 3787–3795.
ista: 'Henzinger TA, Lechner M, Zikelic D. 2021. Scalable verification of quantized
neural networks. Proceedings of the AAAI Conference on Artificial Intelligence.
AAAI: Association for the Advancement of Artificial Intelligence, Technical Tracks,
vol. 35, 3787–3795.'
mla: Henzinger, Thomas A., et al. “Scalable Verification of Quantized Neural Networks.”
Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35,
no. 5A, AAAI Press, 2021, pp. 3787–95.
short: T.A. Henzinger, M. Lechner, D. Zikelic, in:, Proceedings of the AAAI Conference
on Artificial Intelligence, AAAI Press, 2021, pp. 3787–3795.
conference:
end_date: 2021-02-09
location: Virtual
name: 'AAAI: Association for the Advancement of Artificial Intelligence'
start_date: 2021-02-02
date_created: 2022-01-25T15:15:02Z
date_published: 2021-05-28T00:00:00Z
date_updated: 2025-07-14T09:10:11Z
day: '28'
ddc:
- '000'
department:
- _id: GradSch
- _id: ToHe
ec_funded: 1
external_id:
arxiv:
- '2012.08185'
file:
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checksum: 2bc8155b2526a70fba5b7301bc89dbd1
content_type: application/pdf
creator: mlechner
date_created: 2022-01-26T07:41:16Z
date_updated: 2022-01-26T07:41:16Z
file_id: '10684'
file_name: 16496-Article Text-19990-1-2-20210518 (1).pdf
file_size: 137235
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has_accepted_license: '1'
intvolume: ' 35'
issue: 5A
language:
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main_file_link:
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url: https://ojs.aaai.org/index.php/AAAI/article/view/16496
month: '05'
oa: 1
oa_version: Published Version
page: 3787-3795
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Proceedings of the AAAI Conference on Artificial Intelligence
publication_identifier:
eissn:
- 2374-3468
isbn:
- 978-1-57735-866-4
issn:
- 2159-5399
publication_status: published
publisher: AAAI Press
quality_controlled: '1'
related_material:
record:
- id: '11362'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Scalable verification of quantized neural networks
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2021'
...
---
_id: '10694'
abstract:
- lang: eng
text: 'In a two-player zero-sum graph game the players move a token throughout a
graph 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, we hold an “auction”
(bidding) to determine which player moves the token: both players simultaneously
submit bids and the higher bidder moves the token. The bidding mechanisms differ
in their payment schemes. Bidding games were largely studied with variants of
first-price bidding in which only the higher bidder pays his bid. We focus on
all-pay bidding, where both players pay their bids. Finite-duration all-pay bidding
games were studied and shown to be technically more challenging than their first-price
counterparts. We study for the first time, infinite-duration all-pay bidding games.
Our most interesting results are for mean-payoff objectives: we portray a complete
picture for games played on strongly-connected graphs. We study both pure (deterministic)
and mixed (probabilistic) strategies and completely characterize the optimal and
almost-sure (with probability 1) payoffs the players can respectively guarantee.
We show that mean-payoff games under all-pay bidding exhibit the intriguing mathematical
properties of their first-price counterparts; namely, an equivalence with random-turn
games in which in each turn, the player who moves is selected according to a (biased)
coin toss. The equivalences for all-pay bidding are more intricate and unexpected
than for first-price bidding.'
acknowledgement: This research was supported in part by the Austrian Science Fund
(FWF) under grant Z211-N23 (Wittgenstein Award), ERC CoG 863818 (FoRM-SMArt), and
by 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. Infinite-duration all-pay bidding games. In:
Marx D, ed. Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms.
Society for Industrial and Applied Mathematics; 2021:617-636. doi:10.1137/1.9781611976465.38'
apa: 'Avni, G., Jecker, I. R., & Zikelic, D. (2021). Infinite-duration all-pay
bidding games. In D. Marx (Ed.), Proceedings of the 2021 ACM-SIAM Symposium
on Discrete Algorithms (pp. 617–636). Virtual: Society for Industrial and
Applied Mathematics. https://doi.org/10.1137/1.9781611976465.38'
chicago: Avni, Guy, Ismael R Jecker, and Dorde Zikelic. “Infinite-Duration All-Pay
Bidding Games.” In Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms,
edited by Dániel Marx, 617–36. Society for Industrial and Applied Mathematics,
2021. https://doi.org/10.1137/1.9781611976465.38.
ieee: G. Avni, I. R. Jecker, and D. Zikelic, “Infinite-duration all-pay bidding
games,” in Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms,
Virtual, 2021, pp. 617–636.
ista: 'Avni G, Jecker IR, Zikelic D. 2021. Infinite-duration all-pay bidding games.
Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms. SODA: Symposium
on Discrete Algorithms, 617–636.'
mla: Avni, Guy, et al. “Infinite-Duration All-Pay Bidding Games.” Proceedings
of the 2021 ACM-SIAM Symposium on Discrete Algorithms, edited by Dániel Marx,
Society for Industrial and Applied Mathematics, 2021, pp. 617–36, doi:10.1137/1.9781611976465.38.
short: G. Avni, I.R. Jecker, D. Zikelic, in:, D. Marx (Ed.), Proceedings of the
2021 ACM-SIAM Symposium on Discrete Algorithms, Society for Industrial and Applied
Mathematics, 2021, pp. 617–636.
conference:
end_date: 2021-01-13
location: Virtual
name: 'SODA: Symposium on Discrete Algorithms'
start_date: 2021-01-10
date_created: 2022-01-27T12:11:23Z
date_published: 2021-01-01T00:00:00Z
date_updated: 2025-07-14T09:10:12Z
day: '01'
department:
- _id: GradSch
- _id: KrCh
doi: 10.1137/1.9781611976465.38
ec_funded: 1
editor:
- first_name: Dániel
full_name: Marx, Dániel
last_name: Marx
external_id:
arxiv:
- '2005.06636'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2005.06636
month: '01'
oa: 1
oa_version: Preprint
page: 617-636
project:
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Proceedings of the 2021 ACM-SIAM Symposium on Discrete Algorithms
publication_identifier:
isbn:
- 978-1-61197-646-5
publication_status: published
publisher: Society for Industrial and Applied Mathematics
quality_controlled: '1'
scopus_import: '1'
status: public
title: Infinite-duration all-pay bidding games
type: conference
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2021'
...
---
_id: '9644'
abstract:
- lang: eng
text: 'We present a new approach to proving non-termination of non-deterministic
integer programs. Our technique is rather simple but efficient. It relies on a
purely syntactic reversal of the program''s transition system followed by a constraint-based
invariant synthesis with constraints coming from both the original and the reversed
transition system. The latter task is performed by a simple call to an off-the-shelf
SMT-solver, which allows us to leverage the latest advances in SMT-solving. Moreover,
our method offers a combination of features not present (as a whole) in previous
approaches: it handles programs with non-determinism, provides relative completeness
guarantees and supports programs with polynomial arithmetic. The experiments performed
with our prototype tool RevTerm show that our approach, despite its simplicity
and stronger theoretical guarantees, is at least on par with the state-of-the-art
tools, often achieving a non-trivial improvement under a proper configuration
of its parameters.'
acknowledgement: We thank the anonymous reviewers for their helpful comments. This
research was partially supported by the ERCCoG 863818 (ForM-SMArt) and the Czech
Science Foundation grant No. GJ19-15134Y.
article_processing_charge: No
arxiv: 1
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Ehsan Kafshdar
full_name: Goharshady, Ehsan Kafshdar
last_name: Goharshady
- first_name: Petr
full_name: Novotný, Petr
id: 3CC3B868-F248-11E8-B48F-1D18A9856A87
last_name: Novotný
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Chatterjee K, Goharshady EK, Novotný P, Zikelic D. Proving non-termination
by program reversal. In: Proceedings of the 42nd ACM SIGPLAN International
Conference on Programming Language Design and Implementation. Association
for Computing Machinery; 2021:1033-1048. doi:10.1145/3453483.3454093'
apa: 'Chatterjee, K., Goharshady, E. K., Novotný, P., & Zikelic, D. (2021).
Proving non-termination by program reversal. In Proceedings of the 42nd ACM
SIGPLAN International Conference on Programming Language Design and Implementation
(pp. 1033–1048). Online: Association for Computing Machinery. https://doi.org/10.1145/3453483.3454093'
chicago: Chatterjee, Krishnendu, Ehsan Kafshdar Goharshady, Petr Novotný, and Dorde
Zikelic. “Proving Non-Termination by Program Reversal.” In Proceedings of the
42nd ACM SIGPLAN International Conference on Programming Language Design and Implementation,
1033–48. Association for Computing Machinery, 2021. https://doi.org/10.1145/3453483.3454093.
ieee: K. Chatterjee, E. K. Goharshady, P. Novotný, and D. Zikelic, “Proving non-termination
by program reversal,” in Proceedings of the 42nd ACM SIGPLAN International
Conference on Programming Language Design and Implementation, Online, 2021,
pp. 1033–1048.
ista: 'Chatterjee K, Goharshady EK, Novotný P, Zikelic D. 2021. Proving non-termination
by program reversal. Proceedings of the 42nd ACM SIGPLAN International Conference
on Programming Language Design and Implementation. PLDI: Programming Language
Design and Implementation, 1033–1048.'
mla: Chatterjee, Krishnendu, et al. “Proving Non-Termination by Program Reversal.”
Proceedings of the 42nd ACM SIGPLAN International Conference on Programming
Language Design and Implementation, Association for Computing Machinery, 2021,
pp. 1033–48, doi:10.1145/3453483.3454093.
short: K. Chatterjee, E.K. Goharshady, P. Novotný, D. Zikelic, in:, Proceedings
of the 42nd ACM SIGPLAN International Conference on Programming Language Design
and Implementation, Association for Computing Machinery, 2021, pp. 1033–1048.
conference:
end_date: 2021-06-26
location: Online
name: 'PLDI: Programming Language Design and Implementation'
start_date: 2021-06-20
date_created: 2021-07-11T22:01:17Z
date_published: 2021-06-01T00:00:00Z
date_updated: 2025-07-14T09:10:06Z
day: '01'
department:
- _id: KrCh
doi: 10.1145/3453483.3454093
ec_funded: 1
external_id:
arxiv:
- '2104.01189'
isi:
- '000723661700067'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/2104.01189
month: '06'
oa: 1
oa_version: Preprint
page: 1033-1048
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Proceedings of the 42nd ACM SIGPLAN International Conference on Programming
Language Design and Implementation
publication_identifier:
isbn:
- '9781450383912'
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
related_material:
record:
- id: '14539'
relation: dissertation_contains
status: public
scopus_import: '1'
status: public
title: Proving non-termination by program reversal
type: conference
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
year: '2021'
...