---
_id: '14318'
abstract:
- lang: eng
text: "Probabilistic recurrence relations (PRRs) are a standard formalism for describing
the runtime of a randomized algorithm. Given a PRR and a time limit κ, we consider
the tail probability Pr[T≥κ], i.e., the probability that the randomized runtime
T of the PRR exceeds κ. Our focus is the formal analysis of tail bounds that aims
at finding a tight asymptotic upper bound u≥Pr[T≥κ]. To address this problem,
the classical and most well-known approach is the cookbook method by Karp (JACM
1994), while other approaches are mostly limited to deriving tail bounds of specific
PRRs via involved custom analysis.\r\nIn this work, we propose a novel approach
for deriving the common exponentially-decreasing tail bounds for PRRs whose preprocessing
time and random passed sizes observe discrete or (piecewise) uniform distribution
and whose recursive call is either a single procedure call or a divide-and-conquer.
We first establish a theoretical approach via Markov’s inequality, and then instantiate
the theoretical approach with a template-based algorithmic approach via a refined
treatment of exponentiation. Experimental evaluation shows that our algorithmic
approach is capable of deriving tail bounds that are (i) asymptotically tighter
than Karp’s method, (ii) match the best-known manually-derived asymptotic tail
bound for QuickSelect, and (iii) is only slightly worse (with a loglogn factor)
than the manually-proven optimal asymptotic tail bound for QuickSort. Moreover,
our algorithmic approach handles all examples (including realistic PRRs such as
QuickSort, QuickSelect, DiameterComputation, etc.) in less than 0.1 s, showing
that our approach is efficient in practice."
acknowledgement: We thank Prof. Bican Xia for valuable information on the exponential
theory of reals. The work is partially supported by the National Natural Science
Foundation of China (NSFC) with Grant No. 62172271, ERC CoG 863818 (ForM-SMArt),
the Hong Kong Research Grants Council ECS Project Number 26208122, the HKUST-Kaisa
Joint Research Institute Project Grant HKJRI3A-055 and the HKUST Startup Grant R9272.
alternative_title:
- LNCS
article_processing_charge: Yes (in subscription journal)
author:
- first_name: Yican
full_name: Sun, Yican
last_name: Sun
- first_name: Hongfei
full_name: Fu, Hongfei
last_name: Fu
- 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
citation:
ama: 'Sun Y, Fu H, Chatterjee K, Goharshady AK. Automated tail bound analysis for probabilistic
recurrence relations. In: Computer Aided Verification. Vol 13966. Springer
Nature; 2023:16-39. doi:10.1007/978-3-031-37709-9_2'
apa: 'Sun, Y., Fu, H., Chatterjee, K., & Goharshady, A. K. (2023). Automated
tail bound analysis for probabilistic recurrence relations. In Computer Aided
Verification (Vol. 13966, pp. 16–39). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-37709-9_2'
chicago: Sun, Yican, Hongfei Fu, Krishnendu Chatterjee, and Amir Kafshdar Goharshady.
“Automated Tail Bound Analysis for Probabilistic Recurrence Relations.” In Computer
Aided Verification, 13966:16–39. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-37709-9_2.
ieee: Y. Sun, H. Fu, K. Chatterjee, and A. K. Goharshady, “Automated tail bound
analysis for probabilistic recurrence relations,” in Computer Aided Verification,
Paris, France, 2023, vol. 13966, pp. 16–39.
ista: 'Sun Y, Fu H, Chatterjee K, Goharshady AK. 2023. Automated tail bound analysis
for probabilistic recurrence relations. Computer Aided Verification. CAV: Computer
Aided Verification, LNCS, vol. 13966, 16–39.'
mla: Sun, Yican, et al. “Automated Tail Bound Analysis for Probabilistic Recurrence
Relations.” Computer Aided Verification, vol. 13966, Springer Nature, 2023,
pp. 16–39, doi:10.1007/978-3-031-37709-9_2.
short: Y. Sun, H. Fu, K. Chatterjee, A.K. Goharshady, in:, Computer Aided Verification,
Springer Nature, 2023, pp. 16–39.
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: 2025-07-14T09:09:57Z
day: '17'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/978-3-031-37709-9_2
ec_funded: 1
file:
- access_level: open_access
checksum: 42917e086f8c7699f3bccf84f74fe000
content_type: application/pdf
creator: dernst
date_created: 2023-09-20T08:24:47Z
date_updated: 2023-09-20T08:24:47Z
file_id: '14348'
file_name: 2023_LNCS_Sun.pdf
file_size: 624647
relation: main_file
success: 1
file_date_updated: 2023-09-20T08:24:47Z
has_accepted_license: '1'
intvolume: ' 13966'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 16-39
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Computer Aided Verification
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031377082'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
link:
- relation: software
url: https://github.com/boyvolcano/PRR
scopus_import: '1'
status: public
title: Automated tail bound analysis for probabilistic recurrence relations
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: '14417'
abstract:
- lang: eng
text: Entropic risk (ERisk) is an established risk measure in finance, quantifying
risk by an exponential re-weighting of rewards. We study ERisk for the first time
in the context of turn-based stochastic games with the total reward objective.
This gives rise to an objective function that demands the control of systems in
a risk-averse manner. We show that the resulting games are determined and, in
particular, admit optimal memoryless deterministic strategies. This contrasts
risk measures that previously have been considered in the special case of Markov
decision processes and that require randomization and/or memory. We provide several
results on the decidability and the computational complexity of the threshold
problem, i.e. whether the optimal value of ERisk exceeds a given threshold. In
the most general case, the problem is decidable subject to Shanuel’s conjecture.
If all inputs are rational, the resulting threshold problem can be solved using
algebraic numbers, leading to decidability via a polynomial-time reduction to
the existential theory of the reals. Further restrictions on the encoding of the
input allow the solution of the threshold problem in NP∩coNP. Finally, an approximation
algorithm for the optimal value of ERisk is provided.
acknowledgement: "This work was partly funded by the ERC CoG 863818 (ForM-SMArt),
the DFG Grant\r\n389792660 as part of TRR 248 (Foundations of Perspicuous Software
Systems), the Cluster of\r\nExcellence EXC 2050/1 (CeTI, project ID 390696704, as
part of Germany’s Excellence Strategy), and the DFG projects BA-1679/11-1 and BA-1679/12-1."
alternative_title:
- LIPIcs
article_number: '15'
article_processing_charge: Yes
arxiv: 1
author:
- first_name: Christel
full_name: Baier, Christel
last_name: Baier
- 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: Jakob
full_name: Piribauer, Jakob
last_name: Piribauer
citation:
ama: 'Baier C, Chatterjee K, Meggendorfer T, Piribauer J. Entropic risk for turn-based
stochastic games. In: 48th International Symposium on Mathematical Foundations
of Computer Science. Vol 272. Schloss Dagstuhl - Leibniz-Zentrum für Informatik;
2023. doi:10.4230/LIPIcs.MFCS.2023.15'
apa: 'Baier, C., Chatterjee, K., Meggendorfer, T., & Piribauer, J. (2023). Entropic
risk for turn-based stochastic games. In 48th International Symposium on Mathematical
Foundations of Computer Science (Vol. 272). Bordeaux, France: Schloss Dagstuhl
- Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.MFCS.2023.15'
chicago: Baier, Christel, Krishnendu Chatterjee, Tobias Meggendorfer, and Jakob
Piribauer. “Entropic Risk for Turn-Based Stochastic Games.” In 48th International
Symposium on Mathematical Foundations of Computer Science, Vol. 272. Schloss
Dagstuhl - Leibniz-Zentrum für Informatik, 2023. https://doi.org/10.4230/LIPIcs.MFCS.2023.15.
ieee: C. Baier, K. Chatterjee, T. Meggendorfer, and J. Piribauer, “Entropic risk
for turn-based stochastic games,” in 48th International Symposium on Mathematical
Foundations of Computer Science, Bordeaux, France, 2023, vol. 272.
ista: 'Baier C, Chatterjee K, Meggendorfer T, Piribauer J. 2023. Entropic risk for
turn-based stochastic games. 48th International Symposium on Mathematical Foundations
of Computer Science. MFCS: Symposium on Mathematical Foundations of Computer Science,
LIPIcs, vol. 272, 15.'
mla: Baier, Christel, et al. “Entropic Risk for Turn-Based Stochastic Games.” 48th
International Symposium on Mathematical Foundations of Computer Science, vol.
272, 15, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023, doi:10.4230/LIPIcs.MFCS.2023.15.
short: C. Baier, K. Chatterjee, T. Meggendorfer, J. Piribauer, in:, 48th International
Symposium on Mathematical Foundations of Computer Science, Schloss Dagstuhl -
Leibniz-Zentrum für Informatik, 2023.
conference:
end_date: 2023-09-01
location: Bordeaux, France
name: 'MFCS: Symposium on Mathematical Foundations of Computer Science'
start_date: 2023-08-28
date_created: 2023-10-09T09:21:05Z
date_published: 2023-08-21T00:00:00Z
date_updated: 2025-07-14T09:09:57Z
day: '21'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.4230/LIPIcs.MFCS.2023.15
ec_funded: 1
external_id:
arxiv:
- '2307.06611'
file:
- access_level: open_access
checksum: 402281b17ed669bbf149d0fdf68ac201
content_type: application/pdf
creator: dernst
date_created: 2023-10-09T09:19:11Z
date_updated: 2023-10-09T09:19:11Z
file_id: '14418'
file_name: 2023_LIPIcsMFCS_Baier.pdf
file_size: 826843
relation: main_file
success: 1
file_date_updated: 2023-10-09T09:19:11Z
has_accepted_license: '1'
intvolume: ' 272'
language:
- iso: eng
month: '08'
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'
publication: 48th International Symposium on Mathematical Foundations of Computer
Science
publication_identifier:
eissn:
- 1868-8969
isbn:
- '9783959772921'
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
status: public
title: Entropic risk for turn-based stochastic games
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: 272
year: '2023'
...
---
_id: '14456'
abstract:
- lang: eng
text: In this paper, we present novel algorithms that efficiently compute a shortest
reconfiguration sequence between two given dominating sets in trees and interval
graphs under the TOKEN SLIDING model. In this problem, a graph is provided along
with its two dominating sets, which can be imagined as tokens placed on vertices.
The objective is to find a shortest sequence of dominating sets that transforms
one set into the other, with each set in the sequence resulting from sliding a
single token in the previous set. While identifying any sequence has been well
studied, our work presents the first polynomial algorithms for this optimization
variant in the context of dominating sets.
alternative_title:
- LNCS
article_processing_charge: No
arxiv: 1
author:
- first_name: Jan Matyáš
full_name: Křišťan, Jan Matyáš
last_name: Křišťan
- first_name: Jakub
full_name: Svoboda, Jakub
id: 130759D2-D7DD-11E9-87D2-DE0DE6697425
last_name: Svoboda
orcid: 0000-0002-1419-3267
citation:
ama: 'Křišťan JM, Svoboda J. Shortest dominating set reconfiguration under token
sliding. In: 24th International Symposium on Fundamentals of Computation Theory.
Vol 14292. Springer Nature; 2023:333-347. doi:10.1007/978-3-031-43587-4_24'
apa: 'Křišťan, J. M., & Svoboda, J. (2023). Shortest dominating set reconfiguration
under token sliding. In 24th International Symposium on Fundamentals of Computation
Theory (Vol. 14292, pp. 333–347). Trier, Germany: Springer Nature. https://doi.org/10.1007/978-3-031-43587-4_24'
chicago: Křišťan, Jan Matyáš, and Jakub Svoboda. “Shortest Dominating Set Reconfiguration
under Token Sliding.” In 24th International Symposium on Fundamentals of Computation
Theory, 14292:333–47. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-43587-4_24.
ieee: J. M. Křišťan and J. Svoboda, “Shortest dominating set reconfiguration under
token sliding,” in 24th International Symposium on Fundamentals of Computation
Theory, Trier, Germany, 2023, vol. 14292, pp. 333–347.
ista: 'Křišťan JM, Svoboda J. 2023. Shortest dominating set reconfiguration under
token sliding. 24th International Symposium on Fundamentals of Computation Theory.
FCT: Fundamentals of Computation Theory, LNCS, vol. 14292, 333–347.'
mla: Křišťan, Jan Matyáš, and Jakub Svoboda. “Shortest Dominating Set Reconfiguration
under Token Sliding.” 24th International Symposium on Fundamentals of Computation
Theory, vol. 14292, Springer Nature, 2023, pp. 333–47, doi:10.1007/978-3-031-43587-4_24.
short: J.M. Křišťan, J. Svoboda, in:, 24th International Symposium on Fundamentals
of Computation Theory, Springer Nature, 2023, pp. 333–347.
conference:
end_date: 2023-09-21
location: Trier, Germany
name: 'FCT: Fundamentals of Computation Theory'
start_date: 2023-09-18
date_created: 2023-10-29T23:01:16Z
date_published: 2023-09-21T00:00:00Z
date_updated: 2024-01-22T08:10:49Z
day: '21'
department:
- _id: KrCh
doi: 10.1007/978-3-031-43587-4_24
external_id:
arxiv:
- '2307.10847'
intvolume: ' 14292'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2307.10847
month: '09'
oa: 1
oa_version: Preprint
page: 333-347
publication: 24th International Symposium on Fundamentals of Computation Theory
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031435867'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
link:
- relation: erratum
url: https://doi.org/10.1007/978-3-031-43587-4_31
scopus_import: '1'
status: public
title: Shortest dominating set reconfiguration under token sliding
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14292
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
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:
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creator: cchlebak
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file_size: 2116426
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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
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: '14657'
abstract:
- lang: eng
text: 'Natural selection is usually studied between mutants that differ in reproductive
rate, but are subject to the same population structure. Here we explore how natural
selection acts on mutants that have the same reproductive rate, but different
population structures. In our framework, population structure is given by a graph
that specifies where offspring can disperse. The invading mutant disperses offspring
on a different graph than the resident wild-type. We find that more densely connected
dispersal graphs tend to increase the invader’s fixation probability, but the
exact relationship between structure and fixation probability is subtle. We present
three main results. First, we prove that if both invader and resident are on complete
dispersal graphs, then removing a single edge in the invader’s dispersal graph
reduces its fixation probability. Second, we show that for certain island models
higher invader’s connectivity increases its fixation probability, but the magnitude
of the effect depends on the exact layout of the connections. Third, we show that
for lattices the effect of different connectivity is comparable to that of different
fitness: for large population size, the invader’s fixation probability is either
constant or exponentially small, depending on whether it is more or less connected
than the resident.'
acknowledgement: K.C. acknowledges support from the ERC CoG 863818(ForM-SMArt). J.T.
is supported by Center for Foundations ofModern Computer Science (Charles Univ.
project UNCE/SCI/004).
article_number: '20230355'
article_processing_charge: Yes (in subscription journal)
article_type: original
author:
- first_name: Josef
full_name: Tkadlec, Josef
id: 3F24CCC8-F248-11E8-B48F-1D18A9856A87
last_name: Tkadlec
orcid: 0000-0002-1097-9684
- first_name: Kamran
full_name: Kaveh, Kamran
last_name: Kaveh
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Martin A.
full_name: Nowak, Martin A.
last_name: Nowak
citation:
ama: Tkadlec J, Kaveh K, Chatterjee K, Nowak MA. Evolutionary dynamics of mutants
that modify population structure. Journal of the Royal Society, Interface.
2023;20(208). doi:10.1098/rsif.2023.0355
apa: Tkadlec, J., Kaveh, K., Chatterjee, K., & Nowak, M. A. (2023). Evolutionary
dynamics of mutants that modify population structure. Journal of the Royal
Society, Interface. The Royal Society. https://doi.org/10.1098/rsif.2023.0355
chicago: Tkadlec, Josef, Kamran Kaveh, Krishnendu Chatterjee, and Martin A. Nowak.
“Evolutionary Dynamics of Mutants That Modify Population Structure.” Journal
of the Royal Society, Interface. The Royal Society, 2023. https://doi.org/10.1098/rsif.2023.0355.
ieee: J. Tkadlec, K. Kaveh, K. Chatterjee, and M. A. Nowak, “Evolutionary dynamics
of mutants that modify population structure,” Journal of the Royal Society,
Interface, vol. 20, no. 208. The Royal Society, 2023.
ista: Tkadlec J, Kaveh K, Chatterjee K, Nowak MA. 2023. Evolutionary dynamics of
mutants that modify population structure. Journal of the Royal Society, Interface.
20(208), 20230355.
mla: Tkadlec, Josef, et al. “Evolutionary Dynamics of Mutants That Modify Population
Structure.” Journal of the Royal Society, Interface, vol. 20, no. 208,
20230355, The Royal Society, 2023, doi:10.1098/rsif.2023.0355.
short: J. Tkadlec, K. Kaveh, K. Chatterjee, M.A. Nowak, Journal of the Royal Society,
Interface 20 (2023).
date_created: 2023-12-10T23:00:58Z
date_published: 2023-11-29T00:00:00Z
date_updated: 2025-07-14T09:10:00Z
day: '29'
ddc:
- '000'
- '570'
department:
- _id: KrCh
doi: 10.1098/rsif.2023.0355
ec_funded: 1
external_id:
pmid:
- '38016637'
file:
- access_level: open_access
checksum: 2eefab13127c7786dbd33303c482a004
content_type: application/pdf
creator: dernst
date_created: 2023-12-11T11:10:32Z
date_updated: 2023-12-11T11:10:32Z
file_id: '14673'
file_name: 2023_RoyalInterface_Tkadlec.pdf
file_size: 1720243
relation: main_file
success: 1
file_date_updated: 2023-12-11T11:10:32Z
has_accepted_license: '1'
intvolume: ' 20'
issue: '208'
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Journal of the Royal Society, Interface
publication_identifier:
eissn:
- 1742-5662
publication_status: published
publisher: The Royal Society
quality_controlled: '1'
scopus_import: '1'
status: public
title: Evolutionary dynamics of mutants that modify population structure
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: 20
year: '2023'
...
---
_id: '14736'
abstract:
- lang: eng
text: Payment channel networks (PCNs) are a promising technology to improve the
scalability of cryptocurrencies. PCNs, however, face the challenge that the frequent
usage of certain routes may deplete channels in one direction, and hence prevent
further transactions. In order to reap the full potential of PCNs, recharging
and rebalancing mechanisms are required to provision channels, as well as an admission
control logic to decide which transactions to reject in case capacity is insufficient.
This paper presents a formal model of this optimisation problem. In particular,
we consider an online algorithms perspective, where transactions arrive over time
in an unpredictable manner. Our main contributions are competitive online algorithms
which come with provable guarantees over time. We empirically evaluate our algorithms
on randomly generated transactions to compare the average performance of our algorithms
to our theoretical bounds. We also show how this model and approach differs from
related problems in classic communication networks.
acknowledgement: Supported by the German Federal Ministry of Education and Research
(BMBF), grant 16KISK020K (6G-RIC), 2021–2025, and ERC CoG 863818 (ForM-SMArt).
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Mahsa
full_name: Bastankhah, Mahsa
last_name: Bastankhah
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Mohammad Ali
full_name: Maddah-Ali, Mohammad Ali
last_name: Maddah-Ali
- first_name: Stefan
full_name: Schmid, Stefan
last_name: Schmid
- first_name: Jakub
full_name: Svoboda, Jakub
id: 130759D2-D7DD-11E9-87D2-DE0DE6697425
last_name: Svoboda
orcid: 0000-0002-1419-3267
- first_name: Michelle X
full_name: Yeo, Michelle X
id: 2D82B818-F248-11E8-B48F-1D18A9856A87
last_name: Yeo
orcid: 0009-0001-3676-4809
citation:
ama: 'Bastankhah M, Chatterjee K, Maddah-Ali MA, Schmid S, Svoboda J, Yeo MX. R2:
Boosting liquidity in payment channel networks with online admission control.
In: 27th International Conference on Financial Cryptography and Data Security.
Vol 13950. Springer Nature; 2023:309-325. doi:10.1007/978-3-031-47754-6_18'
apa: 'Bastankhah, M., Chatterjee, K., Maddah-Ali, M. A., Schmid, S., Svoboda, J.,
& Yeo, M. X. (2023). R2: Boosting liquidity in payment channel networks with online
admission control. In 27th International Conference on Financial Cryptography
and Data Security (Vol. 13950, pp. 309–325). Bol, Brac, Croatia: Springer
Nature. https://doi.org/10.1007/978-3-031-47754-6_18'
chicago: 'Bastankhah, Mahsa, Krishnendu Chatterjee, Mohammad Ali Maddah-Ali, Stefan
Schmid, Jakub Svoboda, and Michelle X Yeo. “R2: Boosting Liquidity in Payment
Channel Networks with Online Admission Control.” In 27th International Conference
on Financial Cryptography and Data Security, 13950:309–25. Springer Nature,
2023. https://doi.org/10.1007/978-3-031-47754-6_18.'
ieee: 'M. Bastankhah, K. Chatterjee, M. A. Maddah-Ali, S. Schmid, J. Svoboda, and
M. X. Yeo, “R2: Boosting liquidity in payment channel networks with online admission
control,” in 27th International Conference on Financial Cryptography and Data
Security, Bol, Brac, Croatia, 2023, vol. 13950, pp. 309–325.'
ista: 'Bastankhah M, Chatterjee K, Maddah-Ali MA, Schmid S, Svoboda J, Yeo MX. 2023.
R2: Boosting liquidity in payment channel networks with online admission control.
27th International Conference on Financial Cryptography and Data Security. FC:
Financial Cryptography and Data Security, LNCS, vol. 13950, 309–325.'
mla: 'Bastankhah, Mahsa, et al. “R2: Boosting Liquidity in Payment Channel Networks
with Online Admission Control.” 27th International Conference on Financial
Cryptography and Data Security, vol. 13950, Springer Nature, 2023, pp. 309–25,
doi:10.1007/978-3-031-47754-6_18.'
short: M. Bastankhah, K. Chatterjee, M.A. Maddah-Ali, S. Schmid, J. Svoboda, M.X.
Yeo, in:, 27th International Conference on Financial Cryptography and Data Security,
Springer Nature, 2023, pp. 309–325.
conference:
end_date: 2023-05-05
location: Bol, Brac, Croatia
name: 'FC: Financial Cryptography and Data Security'
start_date: 2023-05-01
date_created: 2024-01-08T09:30:22Z
date_published: 2023-12-01T00:00:00Z
date_updated: 2025-07-14T09:10:01Z
day: '01'
department:
- _id: KrCh
- _id: KrPi
doi: 10.1007/978-3-031-47754-6_18
ec_funded: 1
intvolume: ' 13950'
language:
- iso: eng
month: '12'
oa_version: None
page: 309-325
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: 27th International Conference on Financial Cryptography and Data Security
publication_identifier:
eisbn:
- '9783031477546'
eissn:
- 1611-3349
isbn:
- '9783031477539'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
status: public
title: 'R2: Boosting liquidity in payment channel networks with online admission control'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13950
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:
- 0934-5043
publication_status: published
publisher: Association for Computing Machinery
quality_controlled: '1'
related_material:
record:
- id: '10414'
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: '10770'
abstract:
- lang: eng
text: Mathematical models often aim to describe a complicated mechanism in a cohesive
and simple manner. However, reaching perfect balance between being simple enough
or overly simplistic is a challenging task. Frequently, game-theoretic models
have an underlying assumption that players, whenever they choose to execute a
specific action, do so perfectly. In fact, it is rare that action execution perfectly
coincides with intentions of individuals, giving rise to behavioural mistakes.
The concept of incompetence of players was suggested to address this issue in
game-theoretic settings. Under the assumption of incompetence, players have non-zero
probabilities of executing a different strategy from the one they chose, leading
to stochastic outcomes of the interactions. In this article, we survey results
related to the concept of incompetence in classic as well as evolutionary game
theory and provide several new results. We also suggest future extensions of the
model and argue why it is important to take into account behavioural mistakes
when analysing interactions among players in both economic and biological settings.
acknowledgement: "The authors would like to acknowledge stimulating email discussions
with Dr Wayne Lobb of W.A. Lobb LLC on the topic of evolutionary games. We also
thank Dr Thomas Taimre for his input to the material in Sect. 3.\r\nThe authors
would like to acknowledge partial support from the Australian Research Council under
the Discovery grant DP180101602 and support by the European Union’s Horizon 2020
research and innovation program under the Marie Sklodowska-Curie Grant Agreement
#754411."
article_processing_charge: No
article_type: original
author:
- first_name: Thomas
full_name: Graham, Thomas
last_name: Graham
- first_name: Maria
full_name: Kleshnina, Maria
id: 4E21749C-F248-11E8-B48F-1D18A9856A87
last_name: Kleshnina
- first_name: Jerzy A.
full_name: Filar, Jerzy A.
last_name: Filar
citation:
ama: Graham T, Kleshnina M, Filar JA. Where do mistakes lead? A survey of games
with incompetent players. Dynamic Games and Applications. 2023;13:231-264.
doi:10.1007/s13235-022-00425-3
apa: Graham, T., Kleshnina, M., & Filar, J. A. (2023). Where do mistakes lead?
A survey of games with incompetent players. Dynamic Games and Applications.
Springer Nature. https://doi.org/10.1007/s13235-022-00425-3
chicago: Graham, Thomas, Maria Kleshnina, and Jerzy A. Filar. “Where Do Mistakes
Lead? A Survey of Games with Incompetent Players.” Dynamic Games and Applications.
Springer Nature, 2023. https://doi.org/10.1007/s13235-022-00425-3.
ieee: T. Graham, M. Kleshnina, and J. A. Filar, “Where do mistakes lead? A survey
of games with incompetent players,” Dynamic Games and Applications, vol.
13. Springer Nature, pp. 231–264, 2023.
ista: Graham T, Kleshnina M, Filar JA. 2023. Where do mistakes lead? A survey of
games with incompetent players. Dynamic Games and Applications. 13, 231–264.
mla: Graham, Thomas, et al. “Where Do Mistakes Lead? A Survey of Games with Incompetent
Players.” Dynamic Games and Applications, vol. 13, Springer Nature, 2023,
pp. 231–64, doi:10.1007/s13235-022-00425-3.
short: T. Graham, M. Kleshnina, J.A. Filar, Dynamic Games and Applications 13 (2023)
231–264.
date_created: 2022-02-20T23:01:32Z
date_published: 2023-03-01T00:00:00Z
date_updated: 2023-10-04T09:24:30Z
day: '01'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/s13235-022-00425-3
ec_funded: 1
external_id:
isi:
- '000753777100001'
file:
- access_level: open_access
checksum: cd53b07e96f9030ddb348f305e5b58c7
content_type: application/pdf
creator: dernst
date_created: 2022-02-21T08:54:17Z
date_updated: 2022-02-21T08:54:17Z
file_id: '10781'
file_name: 2022_DynamicGamesApplic_Graham.pdf
file_size: 1890512
relation: main_file
success: 1
file_date_updated: 2022-02-21T08:54:17Z
has_accepted_license: '1'
intvolume: ' 13'
isi: 1
language:
- iso: eng
month: '03'
oa: 1
oa_version: Published Version
page: 231-264
project:
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Dynamic Games and Applications
publication_identifier:
eissn:
- 2153-0793
issn:
- 2153-0785
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Where do mistakes lead? A survey of games with incompetent players
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: 13
year: '2023'
...
---
_id: '12170'
abstract:
- lang: eng
text: We present PET, a specialized and highly optimized framework for partial exploration
on probabilistic systems. Over the last decade, several significant advances in
the analysis of Markov decision processes employed partial exploration. In a nutshell,
this idea allows to focus computation on specific parts of the system, guided
by heuristics, while maintaining correctness. In particular, only relevant parts
of the system are constructed on demand, which in turn potentially allows to omit
constructing large parts of the system. Depending on the model, this leads to
dramatic speed-ups, in extreme cases even up to an arbitrary factor. PET unifies
several previous implementations and provides a flexible framework to easily implement
partial exploration for many further problems. Our experimental evaluation shows
significant improvements compared to the previous implementations while vastly
reducing the overhead required to add support for additional properties.
acknowledgement: We thank Pranav Ashok and Maximilian Weininger for their contributions
to spiritual predecessors of PET as well as motivating the initial development of
this tool.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
citation:
ama: 'Meggendorfer T. PET – A partial exploration tool for probabilistic verification.
In: 20th International Symposium on Automated Technology for Verification and
Analysis. Vol 13505. Springer Nature; 2022:320-326. doi:10.1007/978-3-031-19992-9_20'
apa: 'Meggendorfer, T. (2022). PET – A partial exploration tool for probabilistic
verification. In 20th International Symposium on Automated Technology for Verification
and Analysis (Vol. 13505, pp. 320–326). Virtual: Springer Nature. https://doi.org/10.1007/978-3-031-19992-9_20'
chicago: Meggendorfer, Tobias. “PET – A Partial Exploration Tool for Probabilistic
Verification.” In 20th International Symposium on Automated Technology for
Verification and Analysis, 13505:320–26. Springer Nature, 2022. https://doi.org/10.1007/978-3-031-19992-9_20.
ieee: T. Meggendorfer, “PET – A partial exploration tool for probabilistic verification,”
in 20th International Symposium on Automated Technology for Verification and
Analysis, Virtual, 2022, vol. 13505, pp. 320–326.
ista: 'Meggendorfer T. 2022. PET – A partial exploration tool for probabilistic
verification. 20th International Symposium on Automated Technology for Verification
and Analysis. ATVA: Automated Technology for Verification and Analysis, LNCS,
vol. 13505, 320–326.'
mla: Meggendorfer, Tobias. “PET – A Partial Exploration Tool for Probabilistic Verification.”
20th International Symposium on Automated Technology for Verification and Analysis,
vol. 13505, Springer Nature, 2022, pp. 320–26, doi:10.1007/978-3-031-19992-9_20.
short: T. Meggendorfer, in:, 20th International Symposium on Automated Technology
for Verification and Analysis, Springer Nature, 2022, pp. 320–326.
conference:
end_date: 2022-10-28
location: Virtual
name: 'ATVA: Automated Technology for Verification and Analysis'
start_date: 2022-10-25
date_created: 2023-01-12T12:11:07Z
date_published: 2022-10-21T00:00:00Z
date_updated: 2023-09-05T15:11:51Z
day: '21'
department:
- _id: KrCh
doi: 10.1007/978-3-031-19992-9_20
intvolume: ' 13505'
language:
- iso: eng
month: '10'
oa_version: None
page: 320-326
publication: 20th International Symposium on Automated Technology for Verification
and Analysis
publication_identifier:
eisbn:
- '9783031199929'
eissn:
- 1611-3349
isbn:
- '9783031199912'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: PET – A partial exploration tool for probabilistic verification
type: conference
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 13505
year: '2022'
...
---
_id: '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: '12280'
abstract:
- lang: eng
text: 'In repeated interactions, players can use strategies that respond to the
outcome of previous rounds. Much of the existing literature on direct reciprocity
assumes that all competing individuals use the same strategy space. Here, we study
both learning and evolutionary dynamics of players that differ in the strategy
space they explore. We focus on the infinitely repeated donation game and compare
three natural strategy spaces: memory-1 strategies, which consider the last moves
of both players, reactive strategies, which respond to the last move of the co-player,
and unconditional strategies. These three strategy spaces differ in the memory
capacity that is needed. We compute the long term average payoff that is achieved
in a pairwise learning process. We find that smaller strategy spaces can dominate
larger ones. For weak selection, unconditional players dominate both reactive
and memory-1 players. For intermediate selection, reactive players dominate memory-1
players. Only for strong selection and low cost-to-benefit ratio, memory-1 players
dominate the others. We observe that the supergame between strategy spaces can
be a social dilemma: maximum payoff is achieved if both players explore a larger
strategy space, but smaller strategy spaces dominate.'
acknowledgement: "This work was supported by the European Research Council (https://erc.europa.eu/)\r\nCoG
863818 (ForM-SMArt) (to K.C.), and the European Research Council Starting Grant
850529: E-DIRECT (to C.H.). The funders had no role in study design, data collection
and analysis, decision to publish, or preparation of the manuscript."
article_number: e1010149
article_processing_charge: No
article_type: original
author:
- first_name: Laura
full_name: Schmid, Laura
id: 38B437DE-F248-11E8-B48F-1D18A9856A87
last_name: Schmid
orcid: 0000-0002-6978-7329
- first_name: Christian
full_name: Hilbe, Christian
id: 2FDF8F3C-F248-11E8-B48F-1D18A9856A87
last_name: Hilbe
orcid: 0000-0001-5116-955X
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Martin
full_name: Nowak, Martin
last_name: Nowak
citation:
ama: Schmid L, Hilbe C, Chatterjee K, Nowak M. Direct reciprocity between individuals
that use different strategy spaces. PLOS Computational Biology. 2022;18(6).
doi:10.1371/journal.pcbi.1010149
apa: Schmid, L., Hilbe, C., Chatterjee, K., & Nowak, M. (2022). Direct reciprocity
between individuals that use different strategy spaces. PLOS Computational
Biology. Public Library of Science. https://doi.org/10.1371/journal.pcbi.1010149
chicago: Schmid, Laura, Christian Hilbe, Krishnendu Chatterjee, and Martin Nowak.
“Direct Reciprocity between Individuals That Use Different Strategy Spaces.” PLOS
Computational Biology. Public Library of Science, 2022. https://doi.org/10.1371/journal.pcbi.1010149.
ieee: L. Schmid, C. Hilbe, K. Chatterjee, and M. Nowak, “Direct reciprocity between
individuals that use different strategy spaces,” PLOS Computational Biology,
vol. 18, no. 6. Public Library of Science, 2022.
ista: Schmid L, Hilbe C, Chatterjee K, Nowak M. 2022. Direct reciprocity between
individuals that use different strategy spaces. PLOS Computational Biology. 18(6),
e1010149.
mla: Schmid, Laura, et al. “Direct Reciprocity between Individuals That Use Different
Strategy Spaces.” PLOS Computational Biology, vol. 18, no. 6, e1010149,
Public Library of Science, 2022, doi:10.1371/journal.pcbi.1010149.
short: L. Schmid, C. Hilbe, K. Chatterjee, M. Nowak, PLOS Computational Biology
18 (2022).
date_created: 2023-01-16T10:02:51Z
date_published: 2022-06-14T00:00:00Z
date_updated: 2025-07-14T09:09:49Z
day: '14'
ddc:
- '000'
- '570'
department:
- _id: KrCh
doi: 10.1371/journal.pcbi.1010149
ec_funded: 1
external_id:
isi:
- '000843626800031'
pmid:
- '35700167'
file:
- access_level: open_access
checksum: 31b6b311b6731f1658277a9dfff6632c
content_type: application/pdf
creator: dernst
date_created: 2023-01-30T11:28:13Z
date_updated: 2023-01-30T11:28:13Z
file_id: '12460'
file_name: 2022_PlosCompBio_Schmid.pdf
file_size: 3143222
relation: main_file
success: 1
file_date_updated: 2023-01-30T11:28:13Z
has_accepted_license: '1'
intvolume: ' 18'
isi: 1
issue: '6'
keyword:
- Computational Theory and Mathematics
- Cellular and Molecular Neuroscience
- Genetics
- Molecular Biology
- Ecology
- Modeling and Simulation
- Ecology
- Evolution
- Behavior and Systematics
language:
- iso: eng
month: '06'
oa: 1
oa_version: Published Version
pmid: 1
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: PLOS Computational Biology
publication_identifier:
eissn:
- 1553-7358
publication_status: published
publisher: Public Library of Science
quality_controlled: '1'
scopus_import: '1'
status: public
title: Direct reciprocity between individuals that use different strategy spaces
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 18
year: '2022'
...
---
_id: '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: '12568'
abstract:
- lang: eng
text: We treat the problem of risk-aware control for stochastic shortest path (SSP)
on Markov decision processes (MDP). Typically, expectation is considered for SSP,
which however is oblivious to the incurred risk. We present an alternative view,
instead optimizing conditional value-at-risk (CVaR), an established risk measure.
We treat both Markov chains as well as MDP and introduce, through novel insights,
two algorithms, based on linear programming and value iteration, respectively.
Both algorithms offer precise and provably correct solutions. Evaluation of our
prototype implementation shows that risk-aware control is feasible on several
moderately sized models.
article_processing_charge: No
arxiv: 1
author:
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
citation:
ama: 'Meggendorfer T. Risk-aware stochastic shortest path. In: Proceedings of
the 36th AAAI Conference on Artificial Intelligence, AAAI 2022. Vol 36. Association
for the Advancement of Artificial Intelligence; 2022:9858-9867. doi:10.1609/aaai.v36i9.21222'
apa: 'Meggendorfer, T. (2022). Risk-aware stochastic shortest path. In Proceedings
of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022 (Vol. 36,
pp. 9858–9867). Virtual: Association for the Advancement of Artificial Intelligence.
https://doi.org/10.1609/aaai.v36i9.21222'
chicago: Meggendorfer, Tobias. “Risk-Aware Stochastic Shortest Path.” In Proceedings
of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022, 36:9858–67.
Association for the Advancement of Artificial Intelligence, 2022. https://doi.org/10.1609/aaai.v36i9.21222.
ieee: T. Meggendorfer, “Risk-aware stochastic shortest path,” in Proceedings
of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022, Virtual,
2022, vol. 36, no. 9, pp. 9858–9867.
ista: Meggendorfer T. 2022. Risk-aware stochastic shortest path. Proceedings of
the 36th AAAI Conference on Artificial Intelligence, AAAI 2022. Conference on
Artificial Intelligence vol. 36, 9858–9867.
mla: Meggendorfer, Tobias. “Risk-Aware Stochastic Shortest Path.” Proceedings
of the 36th AAAI Conference on Artificial Intelligence, AAAI 2022, vol. 36,
no. 9, Association for the Advancement of Artificial Intelligence, 2022, pp. 9858–67,
doi:10.1609/aaai.v36i9.21222.
short: T. Meggendorfer, in:, Proceedings of the 36th AAAI Conference on Artificial
Intelligence, AAAI 2022, Association for the Advancement of Artificial Intelligence,
2022, pp. 9858–9867.
conference:
end_date: 2022-03-01
location: Virtual
name: Conference on Artificial Intelligence
start_date: 2022-02-22
date_created: 2023-02-19T23:00:56Z
date_published: 2022-06-28T00:00:00Z
date_updated: 2023-02-20T07:19:12Z
day: '28'
department:
- _id: KrCh
doi: 10.1609/aaai.v36i9.21222
external_id:
arxiv:
- '2203.01640'
intvolume: ' 36'
issue: '9'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: ' https://doi.org/10.48550/arXiv.2203.01640'
month: '06'
oa: 1
oa_version: Preprint
page: 9858-9867
publication: Proceedings of the 36th AAAI Conference on Artificial Intelligence, AAAI
2022
publication_identifier:
eissn:
- 2374-3468
isbn:
- '1577358767'
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
scopus_import: '1'
status: public
title: Risk-aware stochastic shortest path
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 36
year: '2022'
...
---
_id: '12677'
abstract:
- lang: eng
text: "In modern sample-driven Prophet Inequality, an adversary chooses a sequence
of n items with values v1,v2,…,vn to be presented to a decision maker (DM). The
process follows in two phases. In the first phase (sampling phase), some items,
possibly selected at random, are revealed to the DM, but she can never accept
them. In the second phase, the DM is presented with the other items in a random
order and online fashion. For each item, she must make an irrevocable decision
to either accept the item and stop the process or reject the item forever and
proceed to the next item. The goal of the DM is to maximize the expected value
as compared to a Prophet (or offline algorithm) that has access to all information.
In this setting, the sampling phase has no cost and is not part of the optimization
process. However, in many scenarios, the samples are obtained as part of the decision-making
process.\r\nWe model this aspect as a two-phase Prophet Inequality where an adversary
chooses a sequence of 2n items with values v1,v2,…,v2n and the items are randomly
ordered. Finally, there are two phases of the Prophet Inequality problem with
the first n-items and the rest of the items, respectively. We show that some basic
algorithms achieve a ratio of at most 0.450. We present an algorithm that achieves
a ratio of at least 0.495. Finally, we show that for every algorithm the ratio
it can achieve is at most 0.502. Hence our algorithm is near-optimal."
acknowledgement: This research was partially supported by the ERC CoG 863818 (ForM-SMArt)
grant.
article_number: '2209.14368'
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: Mona
full_name: Mohammadi, Mona
id: 4363614d-b686-11ed-a7d5-ac9e4a24bc2e
last_name: Mohammadi
- first_name: Raimundo J
full_name: Saona Urmeneta, Raimundo J
id: BD1DF4C4-D767-11E9-B658-BC13E6697425
last_name: Saona Urmeneta
orcid: 0000-0001-5103-038X
citation:
ama: Chatterjee K, Mohammadi M, Saona Urmeneta RJ. Repeated prophet inequality with
near-optimal bounds. arXiv. doi:10.48550/ARXIV.2209.14368
apa: Chatterjee, K., Mohammadi, M., & Saona Urmeneta, R. J. (n.d.). Repeated
prophet inequality with near-optimal bounds. arXiv. https://doi.org/10.48550/ARXIV.2209.14368
chicago: Chatterjee, Krishnendu, Mona Mohammadi, and Raimundo J Saona Urmeneta.
“Repeated Prophet Inequality with Near-Optimal Bounds.” ArXiv, n.d. https://doi.org/10.48550/ARXIV.2209.14368.
ieee: K. Chatterjee, M. Mohammadi, and R. J. Saona Urmeneta, “Repeated prophet inequality
with near-optimal bounds,” arXiv. .
ista: Chatterjee K, Mohammadi M, Saona Urmeneta RJ. Repeated prophet inequality
with near-optimal bounds. arXiv, 2209.14368.
mla: Chatterjee, Krishnendu, et al. “Repeated Prophet Inequality with Near-Optimal
Bounds.” ArXiv, 2209.14368, doi:10.48550/ARXIV.2209.14368.
short: K. Chatterjee, M. Mohammadi, R.J. Saona Urmeneta, ArXiv (n.d.).
date_created: 2023-02-24T12:21:40Z
date_published: 2022-09-28T00:00:00Z
date_updated: 2025-07-14T09:09:51Z
day: '28'
department:
- _id: GradSch
- _id: KrCh
doi: 10.48550/ARXIV.2209.14368
ec_funded: 1
external_id:
arxiv:
- '2209.14368'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: ' https://doi.org/10.48550/arXiv.2209.14368'
month: '09'
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'
publication: arXiv
publication_status: submitted
status: public
title: Repeated prophet inequality with near-optimal bounds
type: preprint
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2022'
...
---
_id: '12775'
abstract:
- lang: eng
text: "We consider the problem of approximating the reachability probabilities in
Markov decision processes (MDP) with uncountable (continuous) state and action
spaces. While there are algorithms that, for special classes of such MDP, provide
a sequence of approximations converging to the true value in the limit, our aim
is to obtain an algorithm with guarantees on the precision of the approximation.\r\nAs
this problem is undecidable in general, assumptions on the MDP are necessary.
Our main contribution is to identify sufficient assumptions that are as weak as
possible, thus approaching the \"boundary\" of which systems can be correctly
and reliably analyzed. To this end, we also argue why each of our assumptions
is necessary for algorithms based on processing finitely many observations.\r\nWe
present two solution variants. The first one provides converging lower bounds
under weaker assumptions than typical ones from previous works concerned with
guarantees. The second one then utilizes stronger assumptions to additionally
provide converging upper bounds. Altogether, we obtain an anytime algorithm, i.e.
yielding a sequence of approximants with known and iteratively improving precision,
converging to the true value in the limit. Besides, due to the generality of our
assumptions, our algorithms are very general templates, readily allowing for various
heuristics from literature in contrast to, e.g., a specific discretization algorithm.
Our theoretical contribution thus paves the way for future practical improvements
without sacrificing correctness guarantees."
acknowledgement: "Kush Grover: The author has been supported by the DFG research training
group GRK\r\n2428 ConVeY.\r\nMaximilian Weininger: The author has been partially
supported by DFG projects 383882557\r\nStatistical Unbounded Verification (SUV)
and 427755713 Group-By Objectives in Probabilistic\r\nVerification (GOPro)"
alternative_title:
- LIPIcs
article_number: '11'
article_processing_charge: No
arxiv: 1
author:
- first_name: Kush
full_name: Grover, Kush
last_name: Grover
- first_name: Jan
full_name: Kretinsky, Jan
id: 44CEF464-F248-11E8-B48F-1D18A9856A87
last_name: Kretinsky
orcid: 0000-0002-8122-2881
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
- first_name: Maimilian
full_name: Weininger, Maimilian
last_name: Weininger
citation:
ama: 'Grover K, Kretinsky J, Meggendorfer T, Weininger M. Anytime guarantees for
reachability in uncountable Markov decision processes. In: 33rd International
Conference on Concurrency Theory . Vol 243. Schloss Dagstuhl - Leibniz-Zentrum
für Informatik; 2022. doi:10.4230/LIPIcs.CONCUR.2022.11'
apa: 'Grover, K., Kretinsky, J., Meggendorfer, T., & Weininger, M. (2022). Anytime
guarantees for reachability in uncountable Markov decision processes. In 33rd
International Conference on Concurrency Theory (Vol. 243). Warsaw, Poland:
Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.CONCUR.2022.11'
chicago: Grover, Kush, Jan Kretinsky, Tobias Meggendorfer, and Maimilian Weininger.
“Anytime Guarantees for Reachability in Uncountable Markov Decision Processes.”
In 33rd International Conference on Concurrency Theory , Vol. 243. Schloss
Dagstuhl - Leibniz-Zentrum für Informatik, 2022. https://doi.org/10.4230/LIPIcs.CONCUR.2022.11.
ieee: K. Grover, J. Kretinsky, T. Meggendorfer, and M. Weininger, “Anytime guarantees
for reachability in uncountable Markov decision processes,” in 33rd International
Conference on Concurrency Theory , Warsaw, Poland, 2022, vol. 243.
ista: 'Grover K, Kretinsky J, Meggendorfer T, Weininger M. 2022. Anytime guarantees
for reachability in uncountable Markov decision processes. 33rd International
Conference on Concurrency Theory . CONCUR: Conference on Concurrency Theory, LIPIcs,
vol. 243, 11.'
mla: Grover, Kush, et al. “Anytime Guarantees for Reachability in Uncountable Markov
Decision Processes.” 33rd International Conference on Concurrency Theory ,
vol. 243, 11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2022, doi:10.4230/LIPIcs.CONCUR.2022.11.
short: K. Grover, J. Kretinsky, T. Meggendorfer, M. Weininger, in:, 33rd International
Conference on Concurrency Theory , Schloss Dagstuhl - Leibniz-Zentrum für Informatik,
2022.
conference:
end_date: 2022-09-16
location: Warsaw, Poland
name: 'CONCUR: Conference on Concurrency Theory'
start_date: 2022-09-13
date_created: 2023-03-28T08:09:32Z
date_published: 2022-09-15T00:00:00Z
date_updated: 2023-09-26T10:43:30Z
day: '15'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.4230/LIPIcs.CONCUR.2022.11
external_id:
arxiv:
- '2008.04824'
file:
- access_level: open_access
checksum: e282e43d3ae0ba6e067b72f4583e13c0
content_type: application/pdf
creator: dernst
date_created: 2023-09-26T10:43:15Z
date_updated: 2023-09-26T10:43:15Z
file_id: '14372'
file_name: 2022_LIPIcS_Grover.pdf
file_size: 960036
relation: main_file
success: 1
file_date_updated: 2023-09-26T10:43:15Z
has_accepted_license: '1'
intvolume: ' 243'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
publication: '33rd International Conference on Concurrency Theory '
publication_identifier:
issn:
- 1868-8969
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
status: public
title: Anytime guarantees for reachability in uncountable Markov decision processes
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 243
year: '2022'
...
---
_id: '9311'
abstract:
- lang: eng
text: 'Partially observable Markov decision processes (POMDPs) are standard models
for dynamic systems with probabilistic and nondeterministic behaviour in uncertain
environments. We prove that in POMDPs with long-run average objective, the decision
maker has approximately optimal strategies with finite memory. This implies notably
that approximating the long-run value is recursively enumerable, as well as a
weak continuity property of the value with respect to the transition function. '
acknowledgement: "Partially supported by Austrian Science Fund (FWF) NFN Grant No
RiSE/SHiNE S11407, by CONICYT Chile through grant PII 20150140, and by ECOS-CONICYT
through grant C15E03.\r\n"
article_processing_charge: No
article_type: original
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: Raimundo J
full_name: Saona Urmeneta, Raimundo J
id: BD1DF4C4-D767-11E9-B658-BC13E6697425
last_name: Saona Urmeneta
orcid: 0000-0001-5103-038X
- first_name: Bruno
full_name: Ziliotto, Bruno
last_name: Ziliotto
citation:
ama: Chatterjee K, Saona Urmeneta RJ, Ziliotto B. Finite-memory strategies in POMDPs
with long-run average objectives. Mathematics of Operations Research. 2022;47(1):100-119.
doi:10.1287/moor.2020.1116
apa: Chatterjee, K., Saona Urmeneta, R. J., & Ziliotto, B. (2022). Finite-memory
strategies in POMDPs with long-run average objectives. Mathematics of Operations
Research. Institute for Operations Research and the Management Sciences. https://doi.org/10.1287/moor.2020.1116
chicago: Chatterjee, Krishnendu, Raimundo J Saona Urmeneta, and Bruno Ziliotto.
“Finite-Memory Strategies in POMDPs with Long-Run Average Objectives.” Mathematics
of Operations Research. Institute for Operations Research and the Management
Sciences, 2022. https://doi.org/10.1287/moor.2020.1116.
ieee: K. Chatterjee, R. J. Saona Urmeneta, and B. Ziliotto, “Finite-memory strategies
in POMDPs with long-run average objectives,” Mathematics of Operations Research,
vol. 47, no. 1. Institute for Operations Research and the Management Sciences,
pp. 100–119, 2022.
ista: Chatterjee K, Saona Urmeneta RJ, Ziliotto B. 2022. Finite-memory strategies
in POMDPs with long-run average objectives. Mathematics of Operations Research.
47(1), 100–119.
mla: Chatterjee, Krishnendu, et al. “Finite-Memory Strategies in POMDPs with Long-Run
Average Objectives.” Mathematics of Operations Research, vol. 47, no. 1,
Institute for Operations Research and the Management Sciences, 2022, pp. 100–19,
doi:10.1287/moor.2020.1116.
short: K. Chatterjee, R.J. Saona Urmeneta, B. Ziliotto, Mathematics of Operations
Research 47 (2022) 100–119.
date_created: 2021-04-08T09:33:31Z
date_published: 2022-02-01T00:00:00Z
date_updated: 2023-09-05T13:16:11Z
day: '01'
department:
- _id: GradSch
- _id: KrCh
doi: 10.1287/moor.2020.1116
external_id:
arxiv:
- '1904.13360'
isi:
- '000731918100001'
intvolume: ' 47'
isi: 1
issue: '1'
keyword:
- Management Science and Operations Research
- General Mathematics
- Computer Science Applications
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://arxiv.org/abs/1904.13360
month: '02'
oa: 1
oa_version: Preprint
page: 100-119
project:
- _id: 25863FF4-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11407
name: Game Theory
publication: Mathematics of Operations Research
publication_identifier:
eissn:
- 1526-5471
issn:
- 0364-765X
publication_status: published
publisher: Institute for Operations Research and the Management Sciences
quality_controlled: '1'
scopus_import: '1'
status: public
title: Finite-memory strategies in POMDPs with long-run average objectives
type: journal_article
user_id: c635000d-4b10-11ee-a964-aac5a93f6ac1
volume: 47
year: '2022'
...
---
_id: '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'
...