---
_id: '15006'
abstract:
- lang: eng
text: Graphical games are a useful framework for modeling the interactions of (selfish)
agents who are connected via an underlying topology and whose behaviors influence
each other. They have wide applications ranging from computer science to economics
and biology. Yet, even though an agent’s payoff only depends on the actions of
their direct neighbors in graphical games, computing the Nash equilibria and making
statements about the convergence time of "natural" local dynamics in particular
can be highly challenging. In this work, we present a novel approach for classifying
complexity of Nash equilibria in graphical games by establishing a connection
to local graph algorithms, a subfield of distributed computing. In particular,
we make the observation that the equilibria of graphical games are equivalent
to locally verifiable labelings (LVL) in graphs; vertex labelings which are verifiable
with constant-round local algorithms. This connection allows us to derive novel
lower bounds on the convergence time to equilibrium of best-response dynamics
in graphical games. Since we establish that distributed convergence can sometimes
be provably slow, we also introduce and give bounds on an intuitive notion of
"time-constrained" inefficiency of best responses. We exemplify how our results
can be used in the implementation of mechanisms that ensure convergence of best
responses to a Nash equilibrium. Our results thus also give insight into the convergence
of strategy-proof algorithms for graphical games, which is still not well understood.
acknowledgement: This work was partially funded by the Academy of Finland, grant 314888,
the European Research Council CoG 863818 (ForM-SMArt), and the Austrian Science
Fund (FWF) project I 4800-N (ADVISE). LS was supported by the Stochastic Analysis
and Application Research Center (SAARC) under National Research Foundation of Korea
grant NRF-2019R1A5A1028324.
alternative_title:
- LIPIcs
article_number: '11'
article_processing_charge: No
arxiv: 1
author:
- first_name: Juho
full_name: Hirvonen, Juho
last_name: Hirvonen
- first_name: Laura
full_name: Schmid, Laura
id: 38B437DE-F248-11E8-B48F-1D18A9856A87
last_name: Schmid
orcid: 0000-0002-6978-7329
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Stefan
full_name: Schmid, Stefan
last_name: Schmid
citation:
ama: 'Hirvonen J, Schmid L, Chatterjee K, Schmid S. On the convergence time in graphical
games: A locality-sensitive approach. In: 27th International Conference on
Principles of Distributed Systems. Vol 286. Schloss Dagstuhl - Leibniz-Zentrum
für Informatik; 2024. doi:10.4230/LIPIcs.OPODIS.2023.11'
apa: 'Hirvonen, J., Schmid, L., Chatterjee, K., & Schmid, S. (2024). On the
convergence time in graphical games: A locality-sensitive approach. In 27th
International Conference on Principles of Distributed Systems (Vol. 286).
Tokyo, Japan: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. https://doi.org/10.4230/LIPIcs.OPODIS.2023.11'
chicago: 'Hirvonen, Juho, Laura Schmid, Krishnendu Chatterjee, and Stefan Schmid.
“On the Convergence Time in Graphical Games: A Locality-Sensitive Approach.” In
27th International Conference on Principles of Distributed Systems, Vol.
286. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024. https://doi.org/10.4230/LIPIcs.OPODIS.2023.11.'
ieee: 'J. Hirvonen, L. Schmid, K. Chatterjee, and S. Schmid, “On the convergence
time in graphical games: A locality-sensitive approach,” in 27th International
Conference on Principles of Distributed Systems, Tokyo, Japan, 2024, vol.
286.'
ista: 'Hirvonen J, Schmid L, Chatterjee K, Schmid S. 2024. On the convergence time
in graphical games: A locality-sensitive approach. 27th International Conference
on Principles of Distributed Systems. OPODIS: Conference on Principles of Distributed
Systems, LIPIcs, vol. 286, 11.'
mla: 'Hirvonen, Juho, et al. “On the Convergence Time in Graphical Games: A Locality-Sensitive
Approach.” 27th International Conference on Principles of Distributed Systems,
vol. 286, 11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024, doi:10.4230/LIPIcs.OPODIS.2023.11.'
short: J. Hirvonen, L. Schmid, K. Chatterjee, S. Schmid, in:, 27th International
Conference on Principles of Distributed Systems, Schloss Dagstuhl - Leibniz-Zentrum
für Informatik, 2024.
conference:
end_date: 2023-12-08
location: Tokyo, Japan
name: 'OPODIS: Conference on Principles of Distributed Systems'
start_date: 2023-12-06
date_created: 2024-02-18T23:01:01Z
date_published: 2024-01-18T00:00:00Z
date_updated: 2025-07-14T09:10:03Z
day: '18'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.4230/LIPIcs.OPODIS.2023.11
ec_funded: 1
external_id:
arxiv:
- '2102.13457'
file:
- access_level: open_access
checksum: 4fc7eea6e4ba140b904781fc7df868ec
content_type: application/pdf
creator: dernst
date_created: 2024-02-26T09:04:58Z
date_updated: 2024-02-26T09:04:58Z
file_id: '15028'
file_name: 2024_LIPICs_Hirvonen.pdf
file_size: 867363
relation: main_file
success: 1
file_date_updated: 2024-02-26T09:04:58Z
has_accepted_license: '1'
intvolume: ' 286'
language:
- iso: eng
month: '01'
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: 27th International Conference on Principles of Distributed Systems
publication_identifier:
isbn:
- '9783959773089'
issn:
- '18688969'
publication_status: published
publisher: Schloss Dagstuhl - Leibniz-Zentrum für Informatik
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'On the convergence time in graphical games: A locality-sensitive approach'
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: 286
year: '2024'
...
---
_id: '14317'
abstract:
- lang: eng
text: "Markov decision processes can be viewed as transformers of probability distributions.
While this view is useful from a practical standpoint to reason about trajectories
of distributions, basic reachability and safety problems are known to be computationally
intractable (i.e., Skolem-hard) to solve in such models. Further, we show that
even for simple examples of MDPs, strategies for safety objectives over distributions
can require infinite memory and randomization.\r\nIn light of this, we present
a novel overapproximation approach to synthesize strategies in an MDP, such that
a safety objective over the distributions is met. More precisely, we develop a
new framework for template-based synthesis of certificates as affine distributional
and inductive invariants for safety objectives in MDPs. We provide two algorithms
within this framework. One can only synthesize memoryless strategies, but has
relative completeness guarantees, while the other can synthesize general strategies.
The runtime complexity of both algorithms is in PSPACE. We implement these algorithms
and show that they can solve several non-trivial examples."
acknowledgement: This work was supported in part by the ERC CoG 863818 (FoRM-SMArt)
and the European Union’s Horizon 2020 research and innovation programme under the
Marie Skłodowska-Curie Grant Agreement No. 665385 as well as DST/CEFIPRA/INRIA project
EQuaVE and SERB Matrices grant MTR/2018/00074.
alternative_title:
- LNCS
article_processing_charge: Yes (in subscription journal)
author:
- first_name: S.
full_name: Akshay, S.
last_name: Akshay
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Akshay S, Chatterjee K, Meggendorfer T, Zikelic D. MDPs as distribution transformers:
Affine invariant synthesis for safety objectives. In: International Conference
on Computer Aided Verification. Vol 13966. Springer Nature; 2023:86-112. doi:10.1007/978-3-031-37709-9_5'
apa: 'Akshay, S., Chatterjee, K., Meggendorfer, T., & Zikelic, D. (2023). MDPs
as distribution transformers: Affine invariant synthesis for safety objectives.
In International Conference on Computer Aided Verification (Vol. 13966,
pp. 86–112). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-37709-9_5'
chicago: 'Akshay, S., Krishnendu Chatterjee, Tobias Meggendorfer, and Dorde Zikelic.
“MDPs as Distribution Transformers: Affine Invariant Synthesis for Safety Objectives.”
In International Conference on Computer Aided Verification, 13966:86–112.
Springer Nature, 2023. https://doi.org/10.1007/978-3-031-37709-9_5.'
ieee: 'S. Akshay, K. Chatterjee, T. Meggendorfer, and D. Zikelic, “MDPs as distribution
transformers: Affine invariant synthesis for safety objectives,” in International
Conference on Computer Aided Verification, Paris, France, 2023, vol. 13966,
pp. 86–112.'
ista: 'Akshay S, Chatterjee K, Meggendorfer T, Zikelic D. 2023. MDPs as distribution
transformers: Affine invariant synthesis for safety objectives. International
Conference on Computer Aided Verification. CAV: Computer Aided Verification, LNCS,
vol. 13966, 86–112.'
mla: 'Akshay, S., et al. “MDPs as Distribution Transformers: Affine Invariant Synthesis
for Safety Objectives.” International Conference on Computer Aided Verification,
vol. 13966, Springer Nature, 2023, pp. 86–112, doi:10.1007/978-3-031-37709-9_5.'
short: S. Akshay, K. Chatterjee, T. Meggendorfer, D. Zikelic, in:, International
Conference on Computer Aided Verification, Springer Nature, 2023, pp. 86–112.
conference:
end_date: 2023-07-22
location: Paris, France
name: 'CAV: Computer Aided Verification'
start_date: 2023-07-17
date_created: 2023-09-10T22:01:12Z
date_published: 2023-07-17T00:00:00Z
date_updated: 2025-07-14T09:09:56Z
day: '17'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/978-3-031-37709-9_5
ec_funded: 1
file:
- access_level: open_access
checksum: f143c8eedf609f20f2aad2eeb496d53f
content_type: application/pdf
creator: dernst
date_created: 2023-09-20T08:46:43Z
date_updated: 2023-09-20T08:46:43Z
file_id: '14349'
file_name: 2023_LNCS_Akshay.pdf
file_size: 531745
relation: main_file
success: 1
file_date_updated: 2023-09-20T08:46:43Z
has_accepted_license: '1'
intvolume: ' 13966'
language:
- iso: eng
month: '07'
oa: 1
oa_version: Published Version
page: 86-112
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: International Conference on Computer Aided Verification
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031377082'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: 'MDPs as distribution transformers: Affine invariant synthesis for safety objectives'
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13966
year: '2023'
...
---
_id: '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: '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: '14830'
abstract:
- lang: eng
text: We study the problem of learning controllers for discrete-time non-linear
stochastic dynamical systems with formal reach-avoid guarantees. This work presents
the first method for providing formal reach-avoid guarantees, which combine and
generalize stability and safety guarantees, with a tolerable probability threshold
p in [0,1] over the infinite time horizon. Our method leverages advances in machine
learning literature and it represents formal certificates as neural networks.
In particular, we learn a certificate in the form of a reach-avoid supermartingale
(RASM), a novel notion that we introduce in this work. Our RASMs provide reachability
and avoidance guarantees by imposing constraints on what can be viewed as a stochastic
extension of level sets of Lyapunov functions for deterministic systems. Our approach
solves several important problems -- it can be used to learn a control policy
from scratch, to verify a reach-avoid specification for a fixed control policy,
or to fine-tune a pre-trained policy if it does not satisfy the reach-avoid specification.
We validate our approach on 3 stochastic non-linear reinforcement learning tasks.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC
CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
article_processing_charge: No
arxiv: 1
author:
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
citation:
ama: 'Zikelic D, Lechner M, Henzinger TA, Chatterjee K. Learning control policies
for stochastic systems with reach-avoid guarantees. In: Proceedings of the
37th AAAI Conference on Artificial Intelligence. Vol 37. Association for the
Advancement of Artificial Intelligence; 2023:11926-11935. doi:10.1609/aaai.v37i10.26407'
apa: 'Zikelic, D., Lechner, M., Henzinger, T. A., & Chatterjee, K. (2023). Learning
control policies for stochastic systems with reach-avoid guarantees. In Proceedings
of the 37th AAAI Conference on Artificial Intelligence (Vol. 37, pp. 11926–11935).
Washington, DC, United States: Association for the Advancement of Artificial Intelligence.
https://doi.org/10.1609/aaai.v37i10.26407'
chicago: Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee.
“Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.”
In Proceedings of the 37th AAAI Conference on Artificial Intelligence,
37:11926–35. Association for the Advancement of Artificial Intelligence, 2023.
https://doi.org/10.1609/aaai.v37i10.26407.
ieee: D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control
policies for stochastic systems with reach-avoid guarantees,” in Proceedings
of the 37th AAAI Conference on Artificial Intelligence, Washington, DC, United
States, 2023, vol. 37, no. 10, pp. 11926–11935.
ista: 'Zikelic D, Lechner M, Henzinger TA, Chatterjee K. 2023. Learning control
policies for stochastic systems with reach-avoid guarantees. Proceedings of the
37th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial
Intelligence vol. 37, 11926–11935.'
mla: Zikelic, Dorde, et al. “Learning Control Policies for Stochastic Systems with
Reach-Avoid Guarantees.” Proceedings of the 37th AAAI Conference on Artificial
Intelligence, vol. 37, no. 10, Association for the Advancement of Artificial
Intelligence, 2023, pp. 11926–35, doi:10.1609/aaai.v37i10.26407.
short: D. Zikelic, M. Lechner, T.A. Henzinger, K. Chatterjee, in:, Proceedings of
the 37th AAAI Conference on Artificial Intelligence, Association for the Advancement
of Artificial Intelligence, 2023, pp. 11926–11935.
conference:
end_date: 2023-02-14
location: Washington, DC, United States
name: 'AAAI: Conference on Artificial Intelligence'
start_date: 2023-02-07
date_created: 2024-01-18T07:44:31Z
date_published: 2023-06-26T00:00:00Z
date_updated: 2025-07-14T09:10:02Z
day: '26'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v37i10.26407
ec_funded: 1
external_id:
arxiv:
- '2210.05308'
intvolume: ' 37'
issue: '10'
keyword:
- General Medicine
language:
- iso: eng
month: '06'
oa_version: Preprint
page: 11926-11935
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Proceedings of the 37th AAAI Conference on Artificial Intelligence
publication_identifier:
eissn:
- 2374-3468
issn:
- 2159-5399
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
related_material:
record:
- id: '14600'
relation: earlier_version
status: public
status: public
title: Learning control policies for stochastic systems with reach-avoid guarantees
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2023'
...
---
_id: '15023'
abstract:
- lang: eng
text: Reinforcement learning has shown promising results in learning neural network
policies for complicated control tasks. However, the lack of formal guarantees
about the behavior of such policies remains an impediment to their deployment.
We propose a novel method for learning a composition of neural network policies
in stochastic environments, along with a formal certificate which guarantees that
a specification over the policy's behavior is satisfied with the desired probability.
Unlike prior work on verifiable RL, our approach leverages the compositional nature
of logical specifications provided in SpectRL, to learn over graphs of probabilistic
reach-avoid specifications. The formal guarantees are provided by learning neural
network policies together with reach-avoid supermartingales (RASM) for the graph’s
sub-tasks and then composing them into a global policy. We also derive a tighter
lower bound compared to previous work on the probability of reach-avoidance implied
by a RASM, which is required to find a compositional policy with an acceptable
probabilistic threshold for complex tasks with multiple edge policies. We implement
a prototype of our approach and evaluate it on a Stochastic Nine Rooms environment.
acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093 (VAMOS)
and the ERC-2020-\r\nCoG 863818 (FoRM-SMArt)."
article_processing_charge: No
arxiv: 1
author:
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Abhinav
full_name: Verma, Abhinav
id: a235593c-d7fa-11eb-a0c5-b22ca3c66ee6
last_name: Verma
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
citation:
ama: 'Zikelic D, Lechner M, Verma A, Chatterjee K, Henzinger TA. Compositional policy
learning in stochastic control systems with formal guarantees. In: 37th Conference
on Neural Information Processing Systems. ; 2023.'
apa: Zikelic, D., Lechner, M., Verma, A., Chatterjee, K., & Henzinger, T. A.
(2023). Compositional policy learning in stochastic control systems with formal
guarantees. In 37th Conference on Neural Information Processing Systems.
New Orleans, LO, United States.
chicago: Zikelic, Dorde, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee,
and Thomas A Henzinger. “Compositional Policy Learning in Stochastic Control Systems
with Formal Guarantees.” In 37th Conference on Neural Information Processing
Systems, 2023.
ieee: D. Zikelic, M. Lechner, A. Verma, K. Chatterjee, and T. A. Henzinger, “Compositional
policy learning in stochastic control systems with formal guarantees,” in 37th
Conference on Neural Information Processing Systems, New Orleans, LO, United
States, 2023.
ista: 'Zikelic D, Lechner M, Verma A, Chatterjee K, Henzinger TA. 2023. Compositional
policy learning in stochastic control systems with formal guarantees. 37th Conference
on Neural Information Processing Systems. NeurIPS: Neural Information Processing
Systems.'
mla: Zikelic, Dorde, et al. “Compositional Policy Learning in Stochastic Control
Systems with Formal Guarantees.” 37th Conference on Neural Information Processing
Systems, 2023.
short: D. Zikelic, M. Lechner, A. Verma, K. Chatterjee, T.A. Henzinger, in:, 37th
Conference on Neural Information Processing Systems, 2023.
conference:
end_date: 2023-12-16
location: New Orleans, LO, United States
name: 'NeurIPS: Neural Information Processing Systems'
start_date: 2023-12-10
date_created: 2024-02-25T09:23:24Z
date_published: 2023-12-15T00:00:00Z
date_updated: 2025-07-14T09:10:04Z
day: '15'
department:
- _id: ToHe
- _id: KrCh
ec_funded: 1
external_id:
arxiv:
- '2312.01456'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2312.01456
month: '12'
oa: 1
oa_version: Preprint
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
publication: 37th Conference on Neural Information Processing Systems
publication_status: epub_ahead
quality_controlled: '1'
status: public
title: Compositional policy learning in stochastic control systems with formal guarantees
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '13142'
abstract:
- lang: eng
text: Reinforcement learning has received much attention for learning controllers
of deterministic systems. We consider a learner-verifier framework for stochastic
control systems and survey recent methods that formally guarantee a conjunction
of reachability and safety properties. Given a property and a lower bound on the
probability of the property being satisfied, our framework jointly learns a control
policy and a formal certificate to ensure the satisfaction of the property with
a desired probability threshold. Both the control policy and the formal certificate
are continuous functions from states to reals, which are learned as parameterized
neural networks. While in the deterministic case, the certificates are invariant
and barrier functions for safety, or Lyapunov and ranking functions for liveness,
in the stochastic case the certificates are supermartingales. For certificate
verification, we use interval arithmetic abstract interpretation to bound the
expected values of neural network functions.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC
CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
citation:
ama: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. A learner-verifier framework
for neural network controllers and certificates of stochastic systems. In: Tools
and Algorithms for the Construction and Analysis of Systems . Vol 13993. Springer
Nature; 2023:3-25. doi:10.1007/978-3-031-30823-9_1'
apa: 'Chatterjee, K., Henzinger, T. A., Lechner, M., & Zikelic, D. (2023). A
learner-verifier framework for neural network controllers and certificates of
stochastic systems. In Tools and Algorithms for the Construction and Analysis
of Systems (Vol. 13993, pp. 3–25). Paris, France: Springer Nature. https://doi.org/10.1007/978-3-031-30823-9_1'
chicago: Chatterjee, Krishnendu, Thomas A Henzinger, Mathias Lechner, and Dorde
Zikelic. “A Learner-Verifier Framework for Neural Network Controllers and Certificates
of Stochastic Systems.” In Tools and Algorithms for the Construction and Analysis
of Systems , 13993:3–25. Springer Nature, 2023. https://doi.org/10.1007/978-3-031-30823-9_1.
ieee: K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic, “A learner-verifier
framework for neural network controllers and certificates of stochastic systems,”
in Tools and Algorithms for the Construction and Analysis of Systems ,
Paris, France, 2023, vol. 13993, pp. 3–25.
ista: 'Chatterjee K, Henzinger TA, Lechner M, Zikelic D. 2023. A learner-verifier
framework for neural network controllers and certificates of stochastic systems.
Tools and Algorithms for the Construction and Analysis of Systems . TACAS: Tools
and Algorithms for the Construction and Analysis of Systems, LNCS, vol. 13993,
3–25.'
mla: Chatterjee, Krishnendu, et al. “A Learner-Verifier Framework for Neural Network
Controllers and Certificates of Stochastic Systems.” Tools and Algorithms for
the Construction and Analysis of Systems , vol. 13993, Springer Nature, 2023,
pp. 3–25, doi:10.1007/978-3-031-30823-9_1.
short: K. Chatterjee, T.A. Henzinger, M. Lechner, D. Zikelic, in:, Tools and Algorithms
for the Construction and Analysis of Systems , Springer Nature, 2023, pp. 3–25.
conference:
end_date: 2023-04-27
location: Paris, France
name: 'TACAS: Tools and Algorithms for the Construction and Analysis of Systems'
start_date: 2023-04-22
date_created: 2023-06-18T22:00:47Z
date_published: 2023-04-22T00:00:00Z
date_updated: 2025-07-14T09:09:52Z
day: '22'
ddc:
- '000'
department:
- _id: KrCh
- _id: ToHe
doi: 10.1007/978-3-031-30823-9_1
ec_funded: 1
file:
- access_level: open_access
checksum: 3d8a8bb24d211bc83360dfc2fd744307
content_type: application/pdf
creator: dernst
date_created: 2023-06-19T08:29:30Z
date_updated: 2023-06-19T08:29:30Z
file_id: '13150'
file_name: 2023_LNCS_Chatterjee.pdf
file_size: 528455
relation: main_file
success: 1
file_date_updated: 2023-06-19T08:29:30Z
has_accepted_license: '1'
intvolume: ' 13993'
language:
- iso: eng
month: '04'
oa: 1
oa_version: Published Version
page: 3-25
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: 'Tools and Algorithms for the Construction and Analysis of Systems '
publication_identifier:
eissn:
- 1611-3349
isbn:
- '9783031308222'
issn:
- 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: A learner-verifier framework for neural network controllers and certificates
of stochastic systems
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13993
year: '2023'
...
---
_id: '13258'
abstract:
- lang: eng
text: Many human interactions feature the characteristics of social dilemmas where
individual actions have consequences for the group and the environment. The feedback
between behavior and environment can be studied with the framework of stochastic
games. In stochastic games, the state of the environment can change, depending
on the choices made by group members. Past work suggests that such feedback can
reinforce cooperative behaviors. In particular, cooperation can evolve in stochastic
games even if it is infeasible in each separate repeated game. In stochastic games,
participants have an interest in conditioning their strategies on the state of
the environment. Yet in many applications, precise information about the state
could be scarce. Here, we study how the availability of information (or lack thereof)
shapes evolution of cooperation. Already for simple examples of two state games
we find surprising effects. In some cases, cooperation is only possible if there
is precise information about the state of the environment. In other cases, cooperation
is most abundant when there is no information about the state of the environment.
We systematically analyze all stochastic games of a given complexity class, to
determine when receiving information about the environment is better, neutral,
or worse for evolution of cooperation.
acknowledgement: 'This work was supported by the European Research Council CoG 863818
(ForM-SMArt) (to K.C.), the European Research Council Starting Grant 850529: E-DIRECT
(to C.H.), the European Union’s Horizon 2020 research and innovation program under
the Marie Sklodowska-Curie Grant Agreement #754411 and the French Agence Nationale
de la Recherche (under the Investissement d’Avenir programme, ANR-17-EURE-0010)
(to M.K.).'
article_number: '4153'
article_processing_charge: Yes
article_type: original
author:
- first_name: Maria
full_name: Kleshnina, Maria
id: 4E21749C-F248-11E8-B48F-1D18A9856A87
last_name: Kleshnina
- first_name: Christian
full_name: Hilbe, Christian
id: 2FDF8F3C-F248-11E8-B48F-1D18A9856A87
last_name: Hilbe
orcid: 0000-0001-5116-955X
- first_name: Stepan
full_name: Simsa, Stepan
id: 409d615c-2f95-11ee-b934-90a352102c1e
last_name: Simsa
orcid: 0000-0001-6687-1210
- 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: Kleshnina M, Hilbe C, Simsa S, Chatterjee K, Nowak MA. The effect of environmental
information on evolution of cooperation in stochastic games. Nature Communications.
2023;14. doi:10.1038/s41467-023-39625-9
apa: Kleshnina, M., Hilbe, C., Simsa, S., Chatterjee, K., & Nowak, M. A. (2023).
The effect of environmental information on evolution of cooperation in stochastic
games. Nature Communications. Springer Nature. https://doi.org/10.1038/s41467-023-39625-9
chicago: Kleshnina, Maria, Christian Hilbe, Stepan Simsa, Krishnendu Chatterjee,
and Martin A. Nowak. “The Effect of Environmental Information on Evolution of
Cooperation in Stochastic Games.” Nature Communications. Springer Nature,
2023. https://doi.org/10.1038/s41467-023-39625-9.
ieee: M. Kleshnina, C. Hilbe, S. Simsa, K. Chatterjee, and M. A. Nowak, “The effect
of environmental information on evolution of cooperation in stochastic games,”
Nature Communications, vol. 14. Springer Nature, 2023.
ista: Kleshnina M, Hilbe C, Simsa S, Chatterjee K, Nowak MA. 2023. The effect of
environmental information on evolution of cooperation in stochastic games. Nature
Communications. 14, 4153.
mla: Kleshnina, Maria, et al. “The Effect of Environmental Information on Evolution
of Cooperation in Stochastic Games.” Nature Communications, vol. 14, 4153,
Springer Nature, 2023, doi:10.1038/s41467-023-39625-9.
short: M. Kleshnina, C. Hilbe, S. Simsa, K. Chatterjee, M.A. Nowak, Nature Communications
14 (2023).
date_created: 2023-07-23T22:01:11Z
date_published: 2023-07-12T00:00:00Z
date_updated: 2025-07-14T09:09:53Z
day: '12'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1038/s41467-023-39625-9
ec_funded: 1
external_id:
isi:
- '001029450400031'
pmid:
- '37438341'
file:
- access_level: open_access
checksum: 5aceefdfe76686267b93ae4fe81899f1
content_type: application/pdf
creator: dernst
date_created: 2023-07-31T11:32:36Z
date_updated: 2023-07-31T11:32:36Z
file_id: '13337'
file_name: 2023_NatureComm_Kleshnina.pdf
file_size: 1601682
relation: main_file
success: 1
file_date_updated: 2023-07-31T11:32:36Z
has_accepted_license: '1'
intvolume: ' 14'
isi: 1
language:
- iso: eng
month: '07'
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'
- _id: 260C2330-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '754411'
name: ISTplus - Postdoctoral Fellowships
publication: Nature Communications
publication_identifier:
eissn:
- 2041-1723
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '13336'
relation: research_data
status: public
scopus_import: '1'
status: public
title: The effect of environmental information on evolution of cooperation in 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: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 14
year: '2023'
...
---
_id: '14242'
abstract:
- lang: eng
text: We study the problem of training and certifying adversarially robust quantized
neural networks (QNNs). Quantization is a technique for making neural networks
more efficient by running them using low-bit integer arithmetic and is therefore
commonly adopted in industry. Recent work has shown that floating-point neural
networks that have been verified to be robust can become vulnerable to adversarial
attacks after quantization, and certification of the quantized representation
is necessary to guarantee robustness. In this work, we present quantization-aware
interval bound propagation (QA-IBP), a novel method for training robust QNNs.
Inspired by advances in robust learning of non-quantized networks, our training
algorithm computes the gradient of an abstract representation of the actual network.
Unlike existing approaches, our method can handle the discrete semantics of QNNs.
Based on QA-IBP, we also develop a complete verification procedure for verifying
the adversarial robustness of QNNs, which is guaranteed to terminate and produce
a correct answer. Compared to existing approaches, the key advantage of our verification
procedure is that it runs entirely on GPU or other accelerator devices. We demonstrate
experimentally that our approach significantly outperforms existing methods and
establish the new state-of-the-art for training and certifying the robustness
of QNNs.
acknowledgement: "This work was supported in part by the ERC-2020-AdG 101020093, ERC
CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
programme under the Marie Skłodowska-Curie Grant Agreement No. 665385. Research
was sponsored by the United\r\nStates Air Force Research Laboratory and the United
States Air Force Artificial Intelligence Accelerator and was accomplished under
Cooperative Agreement Number FA8750-19-2-\r\n1000. The views and conclusions contained
in this document are those of the authors and should not be interpreted as representing
the official policies, either expressed or implied,\r\nof the United States Air
Force or the U.S. Government. The U.S. Government is authorized to reproduce and
distribute reprints for Government purposes notwithstanding any copyright\r\nnotation
herein. The research was also funded in part by the AI2050 program at Schmidt Futures
(Grant G-22-63172) and Capgemini SE."
article_processing_charge: No
arxiv: 1
author:
- first_name: Mathias
full_name: Lechner, Mathias
id: 3DC22916-F248-11E8-B48F-1D18A9856A87
last_name: Lechner
- first_name: Dorde
full_name: Zikelic, Dorde
id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
last_name: Zikelic
orcid: 0000-0002-4681-1699
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Thomas A
full_name: Henzinger, Thomas A
id: 40876CD8-F248-11E8-B48F-1D18A9856A87
last_name: Henzinger
orcid: 0000-0002-2985-7724
- first_name: Daniela
full_name: Rus, Daniela
last_name: Rus
citation:
ama: 'Lechner M, Zikelic D, Chatterjee K, Henzinger TA, Rus D. Quantization-aware
interval bound propagation for training certifiably robust quantized neural networks.
In: Proceedings of the 37th AAAI Conference on Artificial Intelligence.
Vol 37. Association for the Advancement of Artificial Intelligence; 2023:14964-14973.
doi:10.1609/aaai.v37i12.26747'
apa: 'Lechner, M., Zikelic, D., Chatterjee, K., Henzinger, T. A., & Rus, D.
(2023). Quantization-aware interval bound propagation for training certifiably
robust quantized neural networks. In Proceedings of the 37th AAAI Conference
on Artificial Intelligence (Vol. 37, pp. 14964–14973). Washington, DC, United
States: Association for the Advancement of Artificial Intelligence. https://doi.org/10.1609/aaai.v37i12.26747'
chicago: Lechner, Mathias, Dorde Zikelic, Krishnendu Chatterjee, Thomas A Henzinger,
and Daniela Rus. “Quantization-Aware Interval Bound Propagation for Training Certifiably
Robust Quantized Neural Networks.” In Proceedings of the 37th AAAI Conference
on Artificial Intelligence, 37:14964–73. Association for the Advancement of
Artificial Intelligence, 2023. https://doi.org/10.1609/aaai.v37i12.26747.
ieee: M. Lechner, D. Zikelic, K. Chatterjee, T. A. Henzinger, and D. Rus, “Quantization-aware
interval bound propagation for training certifiably robust quantized neural networks,”
in Proceedings of the 37th AAAI Conference on Artificial Intelligence,
Washington, DC, United States, 2023, vol. 37, no. 12, pp. 14964–14973.
ista: 'Lechner M, Zikelic D, Chatterjee K, Henzinger TA, Rus D. 2023. Quantization-aware
interval bound propagation for training certifiably robust quantized neural networks.
Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI: Conference
on Artificial Intelligence vol. 37, 14964–14973.'
mla: Lechner, Mathias, et al. “Quantization-Aware Interval Bound Propagation for
Training Certifiably Robust Quantized Neural Networks.” Proceedings of the
37th AAAI Conference on Artificial Intelligence, vol. 37, no. 12, Association
for the Advancement of Artificial Intelligence, 2023, pp. 14964–73, doi:10.1609/aaai.v37i12.26747.
short: M. Lechner, D. Zikelic, K. Chatterjee, T.A. Henzinger, D. Rus, in:, Proceedings
of the 37th AAAI Conference on Artificial Intelligence, Association for the Advancement
of Artificial Intelligence, 2023, pp. 14964–14973.
conference:
end_date: 2023-02-14
location: Washington, DC, United States
name: 'AAAI: Conference on Artificial Intelligence'
start_date: 2023-02-07
date_created: 2023-08-27T22:01:17Z
date_published: 2023-06-26T00:00:00Z
date_updated: 2025-07-14T09:09:56Z
day: '26'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v37i12.26747
ec_funded: 1
external_id:
arxiv:
- '2211.16187'
intvolume: ' 37'
issue: '12'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.48550/arXiv.2211.16187
month: '06'
oa: 1
oa_version: Preprint
page: 14964-14973
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
call_identifier: H2020
grant_number: '101020093'
name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
call_identifier: H2020
grant_number: '665385'
name: International IST Doctoral Program
publication: Proceedings of the 37th AAAI Conference on Artificial Intelligence
publication_identifier:
isbn:
- '9781577358800'
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
scopus_import: '1'
status: public
title: Quantization-aware interval bound propagation for training certifiably robust
quantized neural networks
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2023'
...
---
_id: '12676'
abstract:
- lang: eng
text: Turn-based stochastic games (aka simple stochastic games) are two-player zero-sum
games played on directed graphs with probabilistic transitions. The goal of player-max
is to maximize the probability to reach a target state against the adversarial
player-min. These games lie in NP ∩ coNP and are among the rare combinatorial
problems that belong to this complexity class for which the existence of polynomial-time
algorithm is a major open question. While randomized sub-exponential time algorithm
exists, all known deterministic algorithms require exponential time in the worst-case.
An important open question has been whether faster algorithms can be obtained
parametrized by the treewidth of the game graph. Even deterministic sub-exponential
time algorithm for constant treewidth turn-based stochastic games has remain elusive.
In this work our main result is a deterministic algorithm to solve turn-based
stochastic games that, given a game with n states, treewidth at most t, and the
bit-complexity of the probabilistic transition function log D, has running time
O ((tn2 log D)t log n). In particular, our algorithm is quasi-polynomial time
for games with constant or poly-logarithmic treewidth.
acknowledgement: This research was partially supported by the ERC CoG 863818 (ForM-SMArt)
grant.
article_processing_charge: No
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Tobias
full_name: Meggendorfer, Tobias
id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
last_name: Meggendorfer
orcid: 0000-0002-1712-2165
- 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: Jakub
full_name: Svoboda, Jakub
id: 130759D2-D7DD-11E9-87D2-DE0DE6697425
last_name: Svoboda
orcid: 0000-0002-1419-3267
citation:
ama: 'Chatterjee K, Meggendorfer T, Saona Urmeneta RJ, Svoboda J. Faster algorithm
for turn-based stochastic games with bounded treewidth. In: Proceedings of
the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms. Society for Industrial
and Applied Mathematics; 2023:4590-4605. doi:10.1137/1.9781611977554.ch173'
apa: 'Chatterjee, K., Meggendorfer, T., Saona Urmeneta, R. J., & Svoboda, J.
(2023). Faster algorithm for turn-based stochastic games with bounded treewidth.
In Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms
(pp. 4590–4605). Florence, Italy: Society for Industrial and Applied Mathematics.
https://doi.org/10.1137/1.9781611977554.ch173'
chicago: Chatterjee, Krishnendu, Tobias Meggendorfer, Raimundo J Saona Urmeneta,
and Jakub Svoboda. “Faster Algorithm for Turn-Based Stochastic Games with Bounded
Treewidth.” In Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete
Algorithms, 4590–4605. Society for Industrial and Applied Mathematics, 2023.
https://doi.org/10.1137/1.9781611977554.ch173.
ieee: K. Chatterjee, T. Meggendorfer, R. J. Saona Urmeneta, and J. Svoboda, “Faster
algorithm for turn-based stochastic games with bounded treewidth,” in Proceedings
of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms, Florence, Italy,
2023, pp. 4590–4605.
ista: 'Chatterjee K, Meggendorfer T, Saona Urmeneta RJ, Svoboda J. 2023. Faster
algorithm for turn-based stochastic games with bounded treewidth. Proceedings
of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms. SODA: Symposium
on Discrete Algorithms, 4590–4605.'
mla: Chatterjee, Krishnendu, et al. “Faster Algorithm for Turn-Based Stochastic
Games with Bounded Treewidth.” Proceedings of the 2023 Annual ACM-SIAM Symposium
on Discrete Algorithms, Society for Industrial and Applied Mathematics, 2023,
pp. 4590–605, doi:10.1137/1.9781611977554.ch173.
short: K. Chatterjee, T. Meggendorfer, R.J. Saona Urmeneta, J. Svoboda, in:, Proceedings
of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms, Society for Industrial
and Applied Mathematics, 2023, pp. 4590–4605.
conference:
end_date: 2023-01-25
location: Florence, Italy
name: 'SODA: Symposium on Discrete Algorithms'
start_date: 2023-01-22
date_created: 2023-02-24T12:20:47Z
date_published: 2023-02-01T00:00:00Z
date_updated: 2025-07-14T09:09:50Z
day: '01'
department:
- _id: GradSch
- _id: KrCh
doi: 10.1137/1.9781611977554.ch173
ec_funded: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1137/1.9781611977554.ch173
month: '02'
oa: 1
oa_version: Published Version
page: 4590-4605
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms
publication_identifier:
isbn:
- '9781611977554'
publication_status: published
publisher: Society for Industrial and Applied Mathematics
quality_controlled: '1'
status: public
title: Faster algorithm for turn-based stochastic games with bounded treewidth
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '12738'
abstract:
- lang: eng
text: We study turn-based stochastic zero-sum games with lexicographic preferences
over objectives. Stochastic games are standard models in control, verification,
and synthesis of stochastic reactive systems that exhibit both randomness as well
as controllable and adversarial non-determinism. Lexicographic order allows one
to consider multiple objectives with a strict preference order. To the best of
our knowledge, stochastic games with lexicographic objectives have not been studied
before. For a mixture of reachability and safety objectives, we show that deterministic
lexicographically optimal strategies exist and memory is only required to remember
the already satisfied and violated objectives. For a constant number of objectives,
we show that the relevant decision problem is in NP∩coNP, matching the current
known bound for single objectives; and in general the decision problem is PSPACE-hard
and can be solved in NEXPTIME∩coNEXPTIME. We present an algorithm that computes
the lexicographically optimal strategies via a reduction to the computation of
optimal strategies in a sequence of single-objectives games. For omega-regular
objectives, we restrict our analysis to one-player games, also known as Markov
decision processes. We show that lexicographically optimal strategies exist and
need either randomization or finite memory. We present an algorithm that solves
the relevant decision problem in polynomial time. We have implemented our algorithms
and report experimental results on various case studies.
acknowledgement: Tobias Winkler and Joost-Pieter Katoen are supported by the DFG RTG
2236 UnRAVeL and the innovation programme under the Marie Skłodowska-Curie grant
agreement No. 101008233 (Mission). Krishnendu Chatterjee is supported by the ERC
CoG 863818 (ForM-SMArt) and the Vienna Science and Technology Fund (WWTF) Project
ICT15-003. Maximilian Weininger is supported by the DFG projects 383882557 Statistical
Unbounded Verification (SUV) and 427755713 Group-By Objectives in Probabilistic
Verification (GOPro). Stefanie Mohr is supported by the DFG RTG 2428 CONVEY. Open
Access funding enabled and organized by Projekt DEAL.
article_processing_charge: No
article_type: original
author:
- first_name: Krishnendu
full_name: Chatterjee, Krishnendu
id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
last_name: Chatterjee
orcid: 0000-0002-4561-241X
- first_name: Joost P
full_name: Katoen, Joost P
id: 4524F760-F248-11E8-B48F-1D18A9856A87
last_name: Katoen
- first_name: Stefanie
full_name: Mohr, Stefanie
last_name: Mohr
- first_name: Maximilian
full_name: Weininger, Maximilian
last_name: Weininger
- first_name: Tobias
full_name: Winkler, Tobias
last_name: Winkler
citation:
ama: Chatterjee K, Katoen JP, Mohr S, Weininger M, Winkler T. Stochastic games with
lexicographic objectives. Formal Methods in System Design. 2023. doi:10.1007/s10703-023-00411-4
apa: Chatterjee, K., Katoen, J. P., Mohr, S., Weininger, M., & Winkler, T. (2023).
Stochastic games with lexicographic objectives. Formal Methods in System Design.
Springer Nature. https://doi.org/10.1007/s10703-023-00411-4
chicago: Chatterjee, Krishnendu, Joost P Katoen, Stefanie Mohr, Maximilian Weininger,
and Tobias Winkler. “Stochastic Games with Lexicographic Objectives.” Formal
Methods in System Design. Springer Nature, 2023. https://doi.org/10.1007/s10703-023-00411-4.
ieee: K. Chatterjee, J. P. Katoen, S. Mohr, M. Weininger, and T. Winkler, “Stochastic
games with lexicographic objectives,” Formal Methods in System Design.
Springer Nature, 2023.
ista: Chatterjee K, Katoen JP, Mohr S, Weininger M, Winkler T. 2023. Stochastic
games with lexicographic objectives. Formal Methods in System Design.
mla: Chatterjee, Krishnendu, et al. “Stochastic Games with Lexicographic Objectives.”
Formal Methods in System Design, Springer Nature, 2023, doi:10.1007/s10703-023-00411-4.
short: K. Chatterjee, J.P. Katoen, S. Mohr, M. Weininger, T. Winkler, Formal Methods
in System Design (2023).
date_created: 2023-03-19T23:00:59Z
date_published: 2023-03-08T00:00:00Z
date_updated: 2025-07-14T09:10:14Z
day: '08'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1007/s10703-023-00411-4
ec_funded: 1
external_id:
isi:
- '000946174300001'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://doi.org/10.1007/s10703-023-00411-4
month: '03'
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: 25892FC0-B435-11E9-9278-68D0E5697425
grant_number: ICT15-003
name: Efficient Algorithms for Computer Aided Verification
publication: Formal Methods in System Design
publication_identifier:
eissn:
- 1572-8102
publication_status: epub_ahead
publisher: Springer Nature
quality_controlled: '1'
related_material:
record:
- id: '8272'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Stochastic games with lexicographic objectives
tmp:
image: /images/cc_by.png
legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
year: '2023'
...
---
_id: '12787'
abstract:
- lang: eng
text: "Populations evolve in spatially heterogeneous environments. While a certain
trait might bring a fitness advantage in some patch of the environment, a different
trait might be advantageous in another patch. Here, we study the Moran birth–death
process with two types of individuals in a population stretched across two patches
of size N, each patch favouring one of the two types. We show that the long-term
fate of such populations crucially depends on the migration rate μ\r\n between
the patches. To classify the possible fates, we use the distinction between polynomial
(short) and exponential (long) timescales. We show that when μ is high then one
of the two types fixates on the whole population after a number of steps that
is only polynomial in N. By contrast, when μ is low then each type holds majority
in the patch where it is favoured for a number of steps that is at least exponential
in N. Moreover, we precisely identify the threshold migration rate μ⋆ that separates
those two scenarios, thereby exactly delineating the situations that support long-term
coexistence of the two types. We also discuss the case of various cycle graphs
and we present computer simulations that perfectly match our analytical results."
acknowledgement: J.S. and K.C. acknowledge support from the ERC CoG 863818 (ForM-SMArt)
article_number: '20220685'
article_processing_charge: No
article_type: original
author:
- first_name: Jakub
full_name: Svoboda, Jakub
id: 130759D2-D7DD-11E9-87D2-DE0DE6697425
last_name: Svoboda
orcid: 0000-0002-1419-3267
- 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
citation:
ama: 'Svoboda J, Tkadlec J, Kaveh K, Chatterjee K. Coexistence times in the Moran
process with environmental heterogeneity. Proceedings of the Royal Society
A: Mathematical, Physical and Engineering Sciences. 2023;479(2271). doi:10.1098/rspa.2022.0685'
apa: 'Svoboda, J., Tkadlec, J., Kaveh, K., & Chatterjee, K. (2023). Coexistence
times in the Moran process with environmental heterogeneity. Proceedings of
the Royal Society A: Mathematical, Physical and Engineering Sciences. The
Royal Society. https://doi.org/10.1098/rspa.2022.0685'
chicago: 'Svoboda, Jakub, Josef Tkadlec, Kamran Kaveh, and Krishnendu Chatterjee.
“Coexistence Times in the Moran Process with Environmental Heterogeneity.” Proceedings
of the Royal Society A: Mathematical, Physical and Engineering Sciences. The
Royal Society, 2023. https://doi.org/10.1098/rspa.2022.0685.'
ieee: 'J. Svoboda, J. Tkadlec, K. Kaveh, and K. Chatterjee, “Coexistence times in
the Moran process with environmental heterogeneity,” Proceedings of the Royal
Society A: Mathematical, Physical and Engineering Sciences, vol. 479, no.
2271. The Royal Society, 2023.'
ista: 'Svoboda J, Tkadlec J, Kaveh K, Chatterjee K. 2023. Coexistence times in the
Moran process with environmental heterogeneity. Proceedings of the Royal Society
A: Mathematical, Physical and Engineering Sciences. 479(2271), 20220685.'
mla: 'Svoboda, Jakub, et al. “Coexistence Times in the Moran Process with Environmental
Heterogeneity.” Proceedings of the Royal Society A: Mathematical, Physical
and Engineering Sciences, vol. 479, no. 2271, 20220685, The Royal Society,
2023, doi:10.1098/rspa.2022.0685.'
short: 'J. Svoboda, J. Tkadlec, K. Kaveh, K. Chatterjee, Proceedings of the Royal
Society A: Mathematical, Physical and Engineering Sciences 479 (2023).'
date_created: 2023-04-02T22:01:09Z
date_published: 2023-03-29T00:00:00Z
date_updated: 2025-07-14T09:09:51Z
day: '29'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1098/rspa.2022.0685
ec_funded: 1
external_id:
isi:
- '000957125500002'
file:
- access_level: open_access
checksum: 13953d349fbefcb5d21ccc6b303297eb
content_type: application/pdf
creator: dernst
date_created: 2023-04-03T06:25:29Z
date_updated: 2023-04-03T06:25:29Z
file_id: '12796'
file_name: 2023_ProceedingsRoyalSocietyA_Svoboda.pdf
file_size: 827784
relation: main_file
success: 1
file_date_updated: 2023-04-03T06:25:29Z
has_accepted_license: '1'
intvolume: ' 479'
isi: 1
issue: '2271'
language:
- iso: eng
month: '03'
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: 'Proceedings of the Royal Society A: Mathematical, Physical and Engineering
Sciences'
publication_identifier:
eissn:
- 1471-2946
issn:
- 1364-5021
publication_status: published
publisher: The Royal Society
quality_controlled: '1'
related_material:
link:
- relation: research_data
url: https://doi.org/10.6084/m9.figshare.21261771.v1
scopus_import: '1'
status: public
title: Coexistence times in the Moran process with environmental heterogeneity
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: 479
year: '2023'
...
---
_id: '12861'
abstract:
- lang: eng
text: The field of indirect reciprocity investigates how social norms can foster
cooperation when individuals continuously monitor and assess each other’s social
interactions. By adhering to certain social norms, cooperating individuals can
improve their reputation and, in turn, receive benefits from others. Eight social
norms, known as the “leading eight," have been shown to effectively promote the
evolution of cooperation as long as information is public and reliable. These
norms categorize group members as either ’good’ or ’bad’. In this study, we examine
a scenario where individuals instead assign nuanced reputation scores to each
other, and only cooperate with those whose reputation exceeds a certain threshold.
We find both analytically and through simulations that such quantitative assessments
are error-correcting, thus facilitating cooperation in situations where information
is private and unreliable. Moreover, our results identify four specific norms
that are robust to such conditions, and may be relevant for helping to sustain
cooperation in natural populations.
acknowledgement: 'This work was supported by the European Research Council CoG 863818
(ForM-SMArt) (to K.C.) and the European Research Council Starting Grant 850529:
E-DIRECT (to C.H.). L.S. received additional partial support by the Austrian Science
Fund (FWF) under grant Z211-N23 (Wittgenstein Award), and also thanks the support
by the Stochastic Analysis and Application Research Center (SAARC) under National
Research Foundation of Korea grant NRF-2019R1A5A1028324. The authors additionally
thank Stefan Schmid for providing access to his lab infrastructure at the University
of Vienna for the purpose of collecting simulation data.'
article_number: '2086'
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: Farbod
full_name: Ekbatani, Farbod
last_name: Ekbatani
- 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
citation:
ama: Schmid L, Ekbatani F, Hilbe C, Chatterjee K. Quantitative assessment can stabilize
indirect reciprocity under imperfect information. Nature Communications.
2023;14. doi:10.1038/s41467-023-37817-x
apa: Schmid, L., Ekbatani, F., Hilbe, C., & Chatterjee, K. (2023). Quantitative
assessment can stabilize indirect reciprocity under imperfect information. Nature
Communications. Springer Nature. https://doi.org/10.1038/s41467-023-37817-x
chicago: Schmid, Laura, Farbod Ekbatani, Christian Hilbe, and Krishnendu Chatterjee.
“Quantitative Assessment Can Stabilize Indirect Reciprocity under Imperfect Information.”
Nature Communications. Springer Nature, 2023. https://doi.org/10.1038/s41467-023-37817-x.
ieee: L. Schmid, F. Ekbatani, C. Hilbe, and K. Chatterjee, “Quantitative assessment
can stabilize indirect reciprocity under imperfect information,” Nature Communications,
vol. 14. Springer Nature, 2023.
ista: Schmid L, Ekbatani F, Hilbe C, Chatterjee K. 2023. Quantitative assessment
can stabilize indirect reciprocity under imperfect information. Nature Communications.
14, 2086.
mla: Schmid, Laura, et al. “Quantitative Assessment Can Stabilize Indirect Reciprocity
under Imperfect Information.” Nature Communications, vol. 14, 2086, Springer
Nature, 2023, doi:10.1038/s41467-023-37817-x.
short: L. Schmid, F. Ekbatani, C. Hilbe, K. Chatterjee, Nature Communications 14
(2023).
date_created: 2023-04-23T22:01:03Z
date_published: 2023-04-12T00:00:00Z
date_updated: 2025-07-14T09:09:52Z
day: '12'
ddc:
- '000'
department:
- _id: KrCh
doi: 10.1038/s41467-023-37817-x
ec_funded: 1
external_id:
isi:
- '001003644100020'
pmid:
- '37045828'
file:
- access_level: open_access
checksum: a4b3b7b36fbef068cabf4fb99501fef6
content_type: application/pdf
creator: dernst
date_created: 2023-04-25T09:13:53Z
date_updated: 2023-04-25T09:13:53Z
file_id: '12868'
file_name: 2023_NatureComm_Schmid.pdf
file_size: 1786475
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file_date_updated: 2023-04-25T09:13:53Z
has_accepted_license: '1'
intvolume: ' 14'
isi: 1
language:
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month: '04'
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'
- _id: 25F42A32-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: Z211
name: The Wittgenstein Prize
publication: Nature Communications
publication_identifier:
eissn:
- 2041-1723
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Quantitative assessment can stabilize indirect reciprocity under imperfect
information
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: 14
year: '2023'
...
---
_id: '10731'
abstract:
- lang: eng
text: Motivated by COVID-19, we develop and analyze a simple stochastic model for
the spread of disease in human population. We track how the number of infected
and critically ill people develops over time in order to estimate the demand that
is imposed on the hospital system. To keep this demand under control, we consider
a class of simple policies for slowing down and reopening society and we compare
their efficiency in mitigating the spread of the virus from several different
points of view. We find that in order to avoid overwhelming of the hospital system,
a policy must impose a harsh lockdown or it must react swiftly (or both). While
reacting swiftly is universally beneficial, being harsh pays off only when the
country is patient about reopening and when the neighboring countries coordinate
their mitigation efforts. Our work highlights the importance of acting decisively
when closing down and the importance of patience and coordination between neighboring
countries when reopening.
acknowledgement: 'K.C. acknowledges support from ERC Consolidator Grant No. (863818:
ForM-SMart). A.P. acknowledges support from FWF Grant No. J-4220. M.A.N. acknowledges
support from Office of Naval Research grant N00014-16-1-2914 and from the John Templeton
Foundation.'
article_number: '1526'
article_processing_charge: No
article_type: original
arxiv: 1
author:
- first_name: Jakub
full_name: Svoboda, Jakub
id: 130759D2-D7DD-11E9-87D2-DE0DE6697425
last_name: Svoboda
orcid: 0000-0002-1419-3267
- first_name: Josef
full_name: Tkadlec, Josef
last_name: Tkadlec
- first_name: Andreas
full_name: Pavlogiannis, Andreas
id: 49704004-F248-11E8-B48F-1D18A9856A87
last_name: Pavlogiannis
orcid: 0000-0002-8943-0722
- 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: Svoboda J, Tkadlec J, Pavlogiannis A, Chatterjee K, Nowak MA. Infection dynamics
of COVID-19 virus under lockdown and reopening. Scientific Reports. 2022;12(1).
doi:10.1038/s41598-022-05333-5
apa: Svoboda, J., Tkadlec, J., Pavlogiannis, A., Chatterjee, K., & Nowak, M.
A. (2022). Infection dynamics of COVID-19 virus under lockdown and reopening.
Scientific Reports. Springer Nature. https://doi.org/10.1038/s41598-022-05333-5
chicago: Svoboda, Jakub, Josef Tkadlec, Andreas Pavlogiannis, Krishnendu Chatterjee,
and Martin A. Nowak. “Infection Dynamics of COVID-19 Virus under Lockdown and
Reopening.” Scientific Reports. Springer Nature, 2022. https://doi.org/10.1038/s41598-022-05333-5.
ieee: J. Svoboda, J. Tkadlec, A. Pavlogiannis, K. Chatterjee, and M. A. Nowak, “Infection
dynamics of COVID-19 virus under lockdown and reopening,” Scientific Reports,
vol. 12, no. 1. Springer Nature, 2022.
ista: Svoboda J, Tkadlec J, Pavlogiannis A, Chatterjee K, Nowak MA. 2022. Infection
dynamics of COVID-19 virus under lockdown and reopening. Scientific Reports. 12(1),
1526.
mla: Svoboda, Jakub, et al. “Infection Dynamics of COVID-19 Virus under Lockdown
and Reopening.” Scientific Reports, vol. 12, no. 1, 1526, Springer Nature,
2022, doi:10.1038/s41598-022-05333-5.
short: J. Svoboda, J. Tkadlec, A. Pavlogiannis, K. Chatterjee, M.A. Nowak, Scientific
Reports 12 (2022).
date_created: 2022-02-06T23:01:30Z
date_published: 2022-01-27T00:00:00Z
date_updated: 2025-07-14T09:10:12Z
day: '27'
ddc:
- '570'
department:
- _id: KrCh
doi: 10.1038/s41598-022-05333-5
ec_funded: 1
external_id:
arxiv:
- '2012.15155'
isi:
- '000749198000039'
file:
- access_level: open_access
checksum: 247afd30c173390940f099ead35a28ed
content_type: application/pdf
creator: alisjak
date_created: 2022-02-07T14:57:59Z
date_updated: 2022-02-07T14:57:59Z
file_id: '10744'
file_name: 2022_ScientificReports_Svoboda.pdf
file_size: 2971922
relation: main_file
success: 1
file_date_updated: 2022-02-07T14:57:59Z
has_accepted_license: '1'
intvolume: ' 12'
isi: 1
issue: '1'
language:
- iso: eng
month: '01'
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: Scientific Reports
publication_identifier:
eissn:
- 2045-2322
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
scopus_import: '1'
status: public
title: Infection dynamics of COVID-19 virus under lockdown and reopening
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: 12
year: '2022'
...
---
_id: '11402'
abstract:
- lang: eng
text: Fixed-horizon planning considers a weighted graph and asks to construct a
path that maximizes the sum of weights for a given time horizon T. However, in
many scenarios, the time horizon is not fixed, but the stopping time is chosen
according to some distribution such that the expected stopping time is T. If the
stopping-time distribution is not known, then to ensure robustness, the distribution
is chosen by an adversary as the worst-case scenario. A stationary plan for every
vertex always chooses the same outgoing edge. For fixed horizon or fixed stopping-time
distribution, stationary plans are not sufficient for optimality. Quite surprisingly
we show that when an adversary chooses the stopping-time distribution with expected
stopping-time T, then stationary plans are sufficient. While computing optimal
stationary plans for fixed horizon is NP-complete, we show that computing optimal
stationary plans under adversarial stopping-time distribution can be achieved
in polynomial time.
acknowledgement: This work was partially supported by Austrian Science Fund (FWF)
NFN Grant No RiSE/SHiNE S11407 and by the grant ERC CoG 863818 (ForM-SMArt).
article_processing_charge: No
article_type: original
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: Laurent
full_name: Doyen, Laurent
last_name: Doyen
citation:
ama: Chatterjee K, Doyen L. Graph planning with expected finite horizon. Journal
of Computer and System Sciences. 2022;129:1-21. doi:10.1016/j.jcss.2022.04.003
apa: Chatterjee, K., & Doyen, L. (2022). Graph planning with expected finite
horizon. Journal of Computer and System Sciences. Elsevier. https://doi.org/10.1016/j.jcss.2022.04.003
chicago: Chatterjee, Krishnendu, and Laurent Doyen. “Graph Planning with Expected
Finite Horizon.” Journal of Computer and System Sciences. Elsevier, 2022.
https://doi.org/10.1016/j.jcss.2022.04.003.
ieee: K. Chatterjee and L. Doyen, “Graph planning with expected finite horizon,”
Journal of Computer and System Sciences, vol. 129. Elsevier, pp. 1–21,
2022.
ista: Chatterjee K, Doyen L. 2022. Graph planning with expected finite horizon.
Journal of Computer and System Sciences. 129, 1–21.
mla: Chatterjee, Krishnendu, and Laurent Doyen. “Graph Planning with Expected Finite
Horizon.” Journal of Computer and System Sciences, vol. 129, Elsevier,
2022, pp. 1–21, doi:10.1016/j.jcss.2022.04.003.
short: K. Chatterjee, L. Doyen, Journal of Computer and System Sciences 129 (2022)
1–21.
date_created: 2022-05-22T22:01:40Z
date_published: 2022-11-01T00:00:00Z
date_updated: 2025-07-14T09:09:54Z
day: '01'
department:
- _id: KrCh
doi: 10.1016/j.jcss.2022.04.003
ec_funded: 1
external_id:
arxiv:
- '1802.03642'
isi:
- '000805002800001'
intvolume: ' 129'
isi: 1
language:
- iso: eng
main_file_link:
- open_access: '1'
url: ' https://doi.org/10.48550/arXiv.1802.03642'
month: '11'
oa: 1
oa_version: Preprint
page: 1-21
project:
- _id: 25863FF4-B435-11E9-9278-68D0E5697425
call_identifier: FWF
grant_number: S11407
name: Game Theory
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
call_identifier: H2020
grant_number: '863818'
name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Journal of Computer and System Sciences
publication_identifier:
eissn:
- 1090-2724
issn:
- 0022-0000
publication_status: published
publisher: Elsevier
quality_controlled: '1'
related_material:
record:
- id: '7402'
relation: earlier_version
status: public
scopus_import: '1'
status: public
title: Graph planning with expected finite horizon
type: journal_article
user_id: 4359f0d1-fa6c-11eb-b949-802e58b17ae8
volume: 129
year: '2022'
...
---
_id: '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'
...