---
_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: <i>27th International Conference on
    Principles of Distributed Systems</i>. Vol 286. Schloss Dagstuhl - Leibniz-Zentrum
    für Informatik; 2024. doi:<a href="https://doi.org/10.4230/LIPIcs.OPODIS.2023.11">10.4230/LIPIcs.OPODIS.2023.11</a>'
  apa: 'Hirvonen, J., Schmid, L., Chatterjee, K., &#38; Schmid, S. (2024). On the
    convergence time in graphical games: A locality-sensitive approach. In <i>27th
    International Conference on Principles of Distributed Systems</i> (Vol. 286).
    Tokyo, Japan: Schloss Dagstuhl - Leibniz-Zentrum für Informatik. <a href="https://doi.org/10.4230/LIPIcs.OPODIS.2023.11">https://doi.org/10.4230/LIPIcs.OPODIS.2023.11</a>'
  chicago: 'Hirvonen, Juho, Laura Schmid, Krishnendu Chatterjee, and Stefan Schmid.
    “On the Convergence Time in Graphical Games: A Locality-Sensitive Approach.” In
    <i>27th International Conference on Principles of Distributed Systems</i>, Vol.
    286. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024. <a href="https://doi.org/10.4230/LIPIcs.OPODIS.2023.11">https://doi.org/10.4230/LIPIcs.OPODIS.2023.11</a>.'
  ieee: 'J. Hirvonen, L. Schmid, K. Chatterjee, and S. Schmid, “On the convergence
    time in graphical games: A locality-sensitive approach,” in <i>27th International
    Conference on Principles of Distributed Systems</i>, 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.” <i>27th International Conference on Principles of Distributed Systems</i>,
    vol. 286, 11, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2024, doi:<a
    href="https://doi.org/10.4230/LIPIcs.OPODIS.2023.11">10.4230/LIPIcs.OPODIS.2023.11</a>.'
  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: <i>International Conference
    on Computer Aided Verification</i>. Vol 13966. Springer Nature; 2023:86-112. doi:<a
    href="https://doi.org/10.1007/978-3-031-37709-9_5">10.1007/978-3-031-37709-9_5</a>'
  apa: 'Akshay, S., Chatterjee, K., Meggendorfer, T., &#38; Zikelic, D. (2023). MDPs
    as distribution transformers: Affine invariant synthesis for safety objectives.
    In <i>International Conference on Computer Aided Verification</i> (Vol. 13966,
    pp. 86–112). Paris, France: Springer Nature. <a href="https://doi.org/10.1007/978-3-031-37709-9_5">https://doi.org/10.1007/978-3-031-37709-9_5</a>'
  chicago: 'Akshay, S., Krishnendu Chatterjee, Tobias Meggendorfer, and Dorde Zikelic.
    “MDPs as Distribution Transformers: Affine Invariant Synthesis for Safety Objectives.”
    In <i>International Conference on Computer Aided Verification</i>, 13966:86–112.
    Springer Nature, 2023. <a href="https://doi.org/10.1007/978-3-031-37709-9_5">https://doi.org/10.1007/978-3-031-37709-9_5</a>.'
  ieee: 'S. Akshay, K. Chatterjee, T. Meggendorfer, and D. Zikelic, “MDPs as distribution
    transformers: Affine invariant synthesis for safety objectives,” in <i>International
    Conference on Computer Aided Verification</i>, 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.” <i>International Conference on Computer Aided Verification</i>,
    vol. 13966, Springer Nature, 2023, pp. 86–112, doi:<a href="https://doi.org/10.1007/978-3-031-37709-9_5">10.1007/978-3-031-37709-9_5</a>.'
  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: <i>Computer Aided Verification</i>. Vol 13966. Springer
    Nature; 2023:16-39. doi:<a href="https://doi.org/10.1007/978-3-031-37709-9_2">10.1007/978-3-031-37709-9_2</a>'
  apa: 'Sun, Y., Fu, H., Chatterjee, K., &#38; Goharshady, A. K. (2023). Automated
    tail bound analysis for probabilistic recurrence relations. In <i>Computer Aided
    Verification</i> (Vol. 13966, pp. 16–39). Paris, France: Springer Nature. <a href="https://doi.org/10.1007/978-3-031-37709-9_2">https://doi.org/10.1007/978-3-031-37709-9_2</a>'
  chicago: Sun, Yican, Hongfei Fu, Krishnendu Chatterjee, and Amir Kafshdar Goharshady.
    “Automated Tail Bound Analysis for Probabilistic Recurrence Relations.” In <i>Computer
    Aided Verification</i>, 13966:16–39. Springer Nature, 2023. <a href="https://doi.org/10.1007/978-3-031-37709-9_2">https://doi.org/10.1007/978-3-031-37709-9_2</a>.
  ieee: Y. Sun, H. Fu, K. Chatterjee, and A. K. Goharshady, “Automated tail bound
    analysis for probabilistic recurrence relations,” in <i>Computer Aided Verification</i>,
    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.” <i>Computer Aided Verification</i>, vol. 13966, Springer Nature, 2023,
    pp. 16–39, doi:<a href="https://doi.org/10.1007/978-3-031-37709-9_2">10.1007/978-3-031-37709-9_2</a>.
  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: <i>48th International Symposium on Mathematical Foundations
    of Computer Science</i>. Vol 272. Schloss Dagstuhl - Leibniz-Zentrum für Informatik;
    2023. doi:<a href="https://doi.org/10.4230/LIPIcs.MFCS.2023.15">10.4230/LIPIcs.MFCS.2023.15</a>'
  apa: 'Baier, C., Chatterjee, K., Meggendorfer, T., &#38; Piribauer, J. (2023). Entropic
    risk for turn-based stochastic games. In <i>48th International Symposium on Mathematical
    Foundations of Computer Science</i> (Vol. 272). Bordeaux, France: Schloss Dagstuhl
    - Leibniz-Zentrum für Informatik. <a href="https://doi.org/10.4230/LIPIcs.MFCS.2023.15">https://doi.org/10.4230/LIPIcs.MFCS.2023.15</a>'
  chicago: Baier, Christel, Krishnendu Chatterjee, Tobias Meggendorfer, and Jakob
    Piribauer. “Entropic Risk for Turn-Based Stochastic Games.” In <i>48th International
    Symposium on Mathematical Foundations of Computer Science</i>, Vol. 272. Schloss
    Dagstuhl - Leibniz-Zentrum für Informatik, 2023. <a href="https://doi.org/10.4230/LIPIcs.MFCS.2023.15">https://doi.org/10.4230/LIPIcs.MFCS.2023.15</a>.
  ieee: C. Baier, K. Chatterjee, T. Meggendorfer, and J. Piribauer, “Entropic risk
    for turn-based stochastic games,” in <i>48th International Symposium on Mathematical
    Foundations of Computer Science</i>, 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.” <i>48th
    International Symposium on Mathematical Foundations of Computer Science</i>, vol.
    272, 15, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2023, doi:<a href="https://doi.org/10.4230/LIPIcs.MFCS.2023.15">10.4230/LIPIcs.MFCS.2023.15</a>.
  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:
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  checksum: 402281b17ed669bbf149d0fdf68ac201
  content_type: application/pdf
  creator: dernst
  date_created: 2023-10-09T09:19:11Z
  date_updated: 2023-10-09T09:19:11Z
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  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: '14518'
abstract:
- lang: eng
  text: We consider bidding games, a class of two-player zero-sum graph games. The
    game proceeds as follows. Both players have bounded budgets. A token is placed
    on a vertex of a graph, in each turn the players simultaneously submit bids, and
    the higher bidder moves the token, where we break bidding ties in favor of Player
    1. Player 1 wins the game iff the token visits a designated target vertex. We
    consider, for the first time, poorman discrete-bidding in which the granularity
    of the bids is restricted and the higher bid is paid to the bank. Previous work
    either did not impose granularity restrictions or considered Richman bidding (bids
    are paid to the opponent). While the latter mechanisms are technically more accessible,
    the former is more appealing from a practical standpoint. Our study focuses on
    threshold budgets, which is the necessary and sufficient initial budget required
    for Player 1 to ensure winning against a given Player 2 budget. We first show
    existence of thresholds. In DAGs, we show that threshold budgets can be approximated
    with error bounds by thresholds under continuous-bidding and that they exhibit
    a periodic behavior. We identify closed-form solutions in special cases. We implement
    and experiment with an algorithm to find threshold budgets.
acknowledgement: This research was supported in part by ISF grant no. 1679/21, ERC
  CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
  programme under the Marie SkłodowskaCurie Grant Agreement No. 665385.
article_processing_charge: No
arxiv: 1
author:
- first_name: Guy
  full_name: Avni, Guy
  id: 463C8BC2-F248-11E8-B48F-1D18A9856A87
  last_name: Avni
  orcid: 0000-0001-5588-8287
- first_name: Tobias
  full_name: Meggendorfer, Tobias
  id: b21b0c15-30a2-11eb-80dc-f13ca25802e1
  last_name: Meggendorfer
  orcid: 0000-0002-1712-2165
- first_name: Suman
  full_name: Sadhukhan, Suman
  last_name: Sadhukhan
- first_name: Josef
  full_name: Tkadlec, Josef
  id: 3F24CCC8-F248-11E8-B48F-1D18A9856A87
  last_name: Tkadlec
  orcid: 0000-0002-1097-9684
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
citation:
  ama: 'Avni G, Meggendorfer T, Sadhukhan S, Tkadlec J, Zikelic D. Reachability poorman
    discrete-bidding games. In: <i>Frontiers in Artificial Intelligence and Applications</i>.
    Vol 372. IOS Press; 2023:141-148. doi:<a href="https://doi.org/10.3233/FAIA230264">10.3233/FAIA230264</a>'
  apa: 'Avni, G., Meggendorfer, T., Sadhukhan, S., Tkadlec, J., &#38; Zikelic, D.
    (2023). Reachability poorman discrete-bidding games. In <i>Frontiers in Artificial
    Intelligence and Applications</i> (Vol. 372, pp. 141–148). Krakow, Poland: IOS
    Press. <a href="https://doi.org/10.3233/FAIA230264">https://doi.org/10.3233/FAIA230264</a>'
  chicago: Avni, Guy, Tobias Meggendorfer, Suman Sadhukhan, Josef Tkadlec, and Dorde
    Zikelic. “Reachability Poorman Discrete-Bidding Games.” In <i>Frontiers in Artificial
    Intelligence and Applications</i>, 372:141–48. IOS Press, 2023. <a href="https://doi.org/10.3233/FAIA230264">https://doi.org/10.3233/FAIA230264</a>.
  ieee: G. Avni, T. Meggendorfer, S. Sadhukhan, J. Tkadlec, and D. Zikelic, “Reachability
    poorman discrete-bidding games,” in <i>Frontiers in Artificial Intelligence and
    Applications</i>, Krakow, Poland, 2023, vol. 372, pp. 141–148.
  ista: 'Avni G, Meggendorfer T, Sadhukhan S, Tkadlec J, Zikelic D. 2023. Reachability
    poorman discrete-bidding games. Frontiers in Artificial Intelligence and Applications.
    ECAI: European Conference on Artificial Intelligence vol. 372, 141–148.'
  mla: Avni, Guy, et al. “Reachability Poorman Discrete-Bidding Games.” <i>Frontiers
    in Artificial Intelligence and Applications</i>, vol. 372, IOS Press, 2023, pp.
    141–48, doi:<a href="https://doi.org/10.3233/FAIA230264">10.3233/FAIA230264</a>.
  short: G. Avni, T. Meggendorfer, S. Sadhukhan, J. Tkadlec, D. Zikelic, in:, Frontiers
    in Artificial Intelligence and Applications, IOS Press, 2023, pp. 141–148.
conference:
  end_date: 2023-10-04
  location: Krakow, Poland
  name: 'ECAI: European Conference on Artificial Intelligence'
  start_date: 2023-09-30
date_created: 2023-11-12T23:00:56Z
date_published: 2023-09-28T00:00:00Z
date_updated: 2025-07-14T09:09:57Z
day: '28'
ddc:
- '000'
department:
- _id: ToHe
- _id: KrCh
doi: 10.3233/FAIA230264
ec_funded: 1
external_id:
  arxiv:
  - '2307.15218'
file:
- access_level: open_access
  checksum: 1390ca38480fa4cf286b0f1a42e8c12f
  content_type: application/pdf
  creator: dernst
  date_created: 2023-11-13T10:16:10Z
  date_updated: 2023-11-13T10:16:10Z
  file_id: '14529'
  file_name: 2023_FAIA_Avni.pdf
  file_size: 501011
  relation: main_file
  success: 1
file_date_updated: 2023-11-13T10:16:10Z
has_accepted_license: '1'
intvolume: '       372'
language:
- iso: eng
month: '09'
oa: 1
oa_version: Published Version
page: 141-148
project:
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: Frontiers in Artificial Intelligence and Applications
publication_identifier:
  isbn:
  - '9781643684369'
  issn:
  - 0922-6389
publication_status: published
publisher: IOS Press
quality_controlled: '1'
scopus_import: '1'
status: public
title: Reachability poorman discrete-bidding games
tmp:
  image: /images/cc_by_nc.png
  legal_code_url: https://creativecommons.org/licenses/by-nc/4.0/legalcode
  name: Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
  short: CC BY-NC (4.0)
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 372
year: '2023'
...
---
_id: '14539'
abstract:
- lang: eng
  text: "Stochastic systems provide a formal framework for modelling and quantifying
    uncertainty in systems and have been widely adopted in many application domains.
    Formal\r\nverification and control of finite state stochastic systems, a subfield
    of formal methods\r\nalso known as probabilistic model checking, is well studied.
    In contrast, formal verification and control of infinite state stochastic systems
    have received comparatively\r\nless attention. However, infinite state stochastic
    systems commonly arise in practice.\r\nFor instance, probabilistic models that
    contain continuous probability distributions such\r\nas normal or uniform, or
    stochastic dynamical systems which are a classical model for\r\ncontrol under
    uncertainty, both give rise to infinite state systems.\r\nThe goal of this thesis
    is to contribute to laying theoretical and algorithmic foundations\r\nof fully
    automated formal verification and control of infinite state stochastic systems,\r\nwith
    a particular focus on systems that may be executed over a long or infinite time.\r\nWe
    consider formal verification of infinite state stochastic systems in the setting
    of\r\nstatic analysis of probabilistic programs and formal control in the setting
    of controller\r\nsynthesis in stochastic dynamical systems. For both problems,
    we present some of the\r\nfirst fully automated methods for probabilistic (a.k.a.
    quantitative) reachability and\r\nsafety analysis applicable to infinite time
    horizon systems. We also advance the state\r\nof the art of probability 1 (a.k.a.
    qualitative) reachability analysis for both problems.\r\nFinally, for formal controller
    synthesis in stochastic dynamical systems, we present a\r\nnovel framework for
    learning neural network control policies in stochastic dynamical\r\nsystems with
    formal guarantees on correctness with respect to quantitative reachability,\r\nsafety
    or reach-avoid specifications.\r\n"
alternative_title:
- ISTA Thesis
article_processing_charge: No
author:
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
citation:
  ama: Zikelic D. Automated verification and control of infinite state stochastic
    systems. 2023. doi:<a href="https://doi.org/10.15479/14539">10.15479/14539</a>
  apa: Zikelic, D. (2023). <i>Automated verification and control of infinite state
    stochastic systems</i>. Institute of Science and Technology Austria. <a href="https://doi.org/10.15479/14539">https://doi.org/10.15479/14539</a>
  chicago: Zikelic, Dorde. “Automated Verification and Control of Infinite State Stochastic
    Systems.” Institute of Science and Technology Austria, 2023. <a href="https://doi.org/10.15479/14539">https://doi.org/10.15479/14539</a>.
  ieee: D. Zikelic, “Automated verification and control of infinite state stochastic
    systems,” Institute of Science and Technology Austria, 2023.
  ista: Zikelic D. 2023. Automated verification and control of infinite state stochastic
    systems. Institute of Science and Technology Austria.
  mla: Zikelic, Dorde. <i>Automated Verification and Control of Infinite State Stochastic
    Systems</i>. Institute of Science and Technology Austria, 2023, doi:<a href="https://doi.org/10.15479/14539">10.15479/14539</a>.
  short: D. Zikelic, Automated Verification and Control of Infinite State Stochastic
    Systems, Institute of Science and Technology Austria, 2023.
date_created: 2023-11-15T13:39:10Z
date_published: 2023-11-15T00:00:00Z
date_updated: 2025-07-14T09:10:10Z
day: '15'
ddc:
- '000'
degree_awarded: PhD
department:
- _id: KrCh
- _id: GradSch
doi: 10.15479/14539
ec_funded: 1
file:
- access_level: open_access
  checksum: f23e002b0059ca78e1fbb864da52dd7e
  content_type: application/pdf
  creator: cchlebak
  date_created: 2023-11-15T13:43:28Z
  date_updated: 2023-11-15T13:43:28Z
  file_id: '14540'
  file_name: main.pdf
  file_size: 2116426
  relation: main_file
  success: 1
- access_level: closed
  checksum: 80ca37618a3c7b59866875f8be9b15ed
  content_type: application/x-zip-compressed
  creator: cchlebak
  date_created: 2023-11-15T13:44:24Z
  date_updated: 2023-11-15T13:44:24Z
  file_id: '14541'
  file_name: thesis_source.zip
  file_size: 35884057
  relation: source_file
file_date_updated: 2023-11-15T13:44:24Z
language:
- iso: eng
month: '11'
oa: 1
oa_version: Published Version
page: '256'
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication_identifier:
  isbn:
  - 978-3-99078-036-7
  issn:
  - 2663 - 337X
publication_status: published
publisher: Institute of Science and Technology Austria
related_material:
  record:
  - id: '1194'
    relation: part_of_dissertation
    status: public
  - id: '12000'
    relation: part_of_dissertation
    status: public
  - id: '12511'
    relation: part_of_dissertation
    status: public
  - id: '14600'
    relation: part_of_dissertation
    status: public
  - id: '14601'
    relation: part_of_dissertation
    status: public
  - id: '9644'
    relation: part_of_dissertation
    status: public
  - id: '10414'
    relation: part_of_dissertation
    status: public
status: public
supervisor:
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
title: Automated verification and control of infinite state stochastic systems
tmp:
  image: /images/cc_by_nc_sa.png
  legal_code_url: https://creativecommons.org/licenses/by-nc-sa/4.0/legalcode
  name: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC
    BY-NC-SA 4.0)
  short: CC BY-NC-SA (4.0)
type: dissertation
user_id: 8b945eb4-e2f2-11eb-945a-df72226e66a9
year: '2023'
...
---
_id: '14559'
abstract:
- lang: eng
  text: We consider the problem of learning control policies in discrete-time stochastic
    systems which guarantee that the system stabilizes within some specified stabilization
    region with probability 1. Our approach is based on the novel notion of stabilizing
    ranking supermartingales (sRSMs) that we introduce in this work. Our sRSMs overcome
    the limitation of methods proposed in previous works whose applicability is restricted
    to systems in which the stabilizing region cannot be left once entered under any
    control policy. We present a learning procedure that learns a control policy together
    with an sRSM that formally certifies probability 1 stability, both learned as
    neural networks. We show that this procedure can also be adapted to formally verifying
    that, under a given Lipschitz continuous control policy, the stochastic system
    stabilizes within some stabilizing region with probability 1. Our experimental
    evaluation shows that our learning procedure can successfully learn provably stabilizing
    policies in practice.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC
  CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
  programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
alternative_title:
- LNCS
article_processing_charge: No
author:
- first_name: Matin
  full_name: Ansaripour, Matin
  last_name: Ansaripour
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
- first_name: Mathias
  full_name: Lechner, Mathias
  id: 3DC22916-F248-11E8-B48F-1D18A9856A87
  last_name: Lechner
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
citation:
  ama: 'Ansaripour M, Chatterjee K, Henzinger TA, Lechner M, Zikelic D. Learning provably
    stabilizing neural controllers for discrete-time stochastic systems. In: <i>21st
    International Symposium on Automated Technology for Verification and Analysis</i>.
    Vol 14215. Springer Nature; 2023:357-379. doi:<a href="https://doi.org/10.1007/978-3-031-45329-8_17">10.1007/978-3-031-45329-8_17</a>'
  apa: 'Ansaripour, M., Chatterjee, K., Henzinger, T. A., Lechner, M., &#38; Zikelic,
    D. (2023). Learning provably stabilizing neural controllers for discrete-time
    stochastic systems. In <i>21st International Symposium on Automated Technology
    for Verification and Analysis</i> (Vol. 14215, pp. 357–379). Singapore, Singapore:
    Springer Nature. <a href="https://doi.org/10.1007/978-3-031-45329-8_17">https://doi.org/10.1007/978-3-031-45329-8_17</a>'
  chicago: Ansaripour, Matin, Krishnendu Chatterjee, Thomas A Henzinger, Mathias Lechner,
    and Dorde Zikelic. “Learning Provably Stabilizing Neural Controllers for Discrete-Time
    Stochastic Systems.” In <i>21st International Symposium on Automated Technology
    for Verification and Analysis</i>, 14215:357–79. Springer Nature, 2023. <a href="https://doi.org/10.1007/978-3-031-45329-8_17">https://doi.org/10.1007/978-3-031-45329-8_17</a>.
  ieee: M. Ansaripour, K. Chatterjee, T. A. Henzinger, M. Lechner, and D. Zikelic,
    “Learning provably stabilizing neural controllers for discrete-time stochastic
    systems,” in <i>21st International Symposium on Automated Technology for Verification
    and Analysis</i>, 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.” <i>21st International Symposium on Automated
    Technology for Verification and Analysis</i>, vol. 14215, Springer Nature, 2023,
    pp. 357–79, doi:<a href="https://doi.org/10.1007/978-3-031-45329-8_17">10.1007/978-3-031-45329-8_17</a>.
  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. <i>Journal of the Royal Society, Interface</i>.
    2023;20(208). doi:<a href="https://doi.org/10.1098/rsif.2023.0355">10.1098/rsif.2023.0355</a>
  apa: Tkadlec, J., Kaveh, K., Chatterjee, K., &#38; Nowak, M. A. (2023). Evolutionary
    dynamics of mutants that modify population structure. <i>Journal of the Royal
    Society, Interface</i>. The Royal Society. <a href="https://doi.org/10.1098/rsif.2023.0355">https://doi.org/10.1098/rsif.2023.0355</a>
  chicago: Tkadlec, Josef, Kamran Kaveh, Krishnendu Chatterjee, and Martin A. Nowak.
    “Evolutionary Dynamics of Mutants That Modify Population Structure.” <i>Journal
    of the Royal Society, Interface</i>. The Royal Society, 2023. <a href="https://doi.org/10.1098/rsif.2023.0355">https://doi.org/10.1098/rsif.2023.0355</a>.
  ieee: J. Tkadlec, K. Kaveh, K. Chatterjee, and M. A. Nowak, “Evolutionary dynamics
    of mutants that modify population structure,” <i>Journal of the Royal Society,
    Interface</i>, 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.” <i>Journal of the Royal Society, Interface</i>, vol. 20, no. 208,
    20230355, The Royal Society, 2023, doi:<a href="https://doi.org/10.1098/rsif.2023.0355">10.1098/rsif.2023.0355</a>.
  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
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  date_updated: 2023-12-11T11:10:32Z
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  file_size: 1720243
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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: <i>27th International Conference on Financial Cryptography and Data Security</i>.
    Vol 13950. Springer Nature; 2023:309-325. doi:<a href="https://doi.org/10.1007/978-3-031-47754-6_18">10.1007/978-3-031-47754-6_18</a>'
  apa: 'Bastankhah, M., Chatterjee, K., Maddah-Ali, M. A., Schmid, S., Svoboda, J.,
    &#38; Yeo, M. X. (2023). R2: Boosting liquidity in payment channel networks with online
    admission control. In <i>27th International Conference on Financial Cryptography
    and Data Security</i> (Vol. 13950, pp. 309–325). Bol, Brac, Croatia: Springer
    Nature. <a href="https://doi.org/10.1007/978-3-031-47754-6_18">https://doi.org/10.1007/978-3-031-47754-6_18</a>'
  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 <i>27th International Conference
    on Financial Cryptography and Data Security</i>, 13950:309–25. Springer Nature,
    2023. <a href="https://doi.org/10.1007/978-3-031-47754-6_18">https://doi.org/10.1007/978-3-031-47754-6_18</a>.'
  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 <i>27th International Conference on Financial Cryptography and Data
    Security</i>, 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.” <i>27th International Conference on Financial
    Cryptography and Data Security</i>, vol. 13950, Springer Nature, 2023, pp. 309–25,
    doi:<a href="https://doi.org/10.1007/978-3-031-47754-6_18">10.1007/978-3-031-47754-6_18</a>.'
  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. <i>Formal Aspects of
    Computing</i>. 2023;35(2). doi:<a href="https://doi.org/10.1145/3585391">10.1145/3585391</a>
  apa: Chatterjee, K., Kafshdar Goharshady, E., Novotný, P., Zárevúcky, J., &#38;
    Zikelic, D. (2023). On lexicographic proof rules for probabilistic termination.
    <i>Formal Aspects of Computing</i>. Association for Computing Machinery. <a href="https://doi.org/10.1145/3585391">https://doi.org/10.1145/3585391</a>
  chicago: Chatterjee, Krishnendu, Ehsan Kafshdar Goharshady, Petr Novotný, Jiří Zárevúcky,
    and Dorde Zikelic. “On Lexicographic Proof Rules for Probabilistic Termination.”
    <i>Formal Aspects of Computing</i>. Association for Computing Machinery, 2023.
    <a href="https://doi.org/10.1145/3585391">https://doi.org/10.1145/3585391</a>.
  ieee: K. Chatterjee, E. Kafshdar Goharshady, P. Novotný, J. Zárevúcky, and D. Zikelic,
    “On lexicographic proof rules for probabilistic termination,” <i>Formal Aspects
    of Computing</i>, 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.” <i>Formal Aspects of Computing</i>, vol. 35, no. 2, 11, Association
    for Computing Machinery, 2023, doi:<a href="https://doi.org/10.1145/3585391">10.1145/3585391</a>.
  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:
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    relation: earlier_version
    status: public
status: public
title: On lexicographic proof rules for probabilistic termination
tmp:
  image: /images/cc_by.png
  legal_code_url: https://creativecommons.org/licenses/by/4.0/legalcode
  name: Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)
  short: CC BY (4.0)
type: journal_article
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 35
year: '2023'
...
---
_id: '14830'
abstract:
- lang: eng
  text: We study the problem of learning controllers for discrete-time non-linear
    stochastic dynamical systems with formal reach-avoid guarantees. This work presents
    the first method for providing formal reach-avoid guarantees, which combine and
    generalize stability and safety guarantees, with a tolerable probability threshold
    p in [0,1] over the infinite time horizon. Our method leverages advances in machine
    learning literature and it represents formal certificates as neural networks.
    In particular, we learn a certificate in the form of a reach-avoid supermartingale
    (RASM), a novel notion that we introduce in this work. Our RASMs provide reachability
    and avoidance guarantees by imposing constraints on what can be viewed as a stochastic
    extension of level sets of Lyapunov functions for deterministic systems. Our approach
    solves several important problems -- it can be used to learn a control policy
    from scratch, to verify a reach-avoid specification for a fixed control policy,
    or to fine-tune a pre-trained policy if it does not satisfy the reach-avoid specification.
    We validate our approach on 3 stochastic non-linear reinforcement learning tasks.
acknowledgement: This work was supported in part by the ERC-2020-AdG 101020093, ERC
  CoG 863818 (FoRM-SMArt) and the European Union’s Horizon 2020 research and innovation
  programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
article_processing_charge: No
arxiv: 1
author:
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
- first_name: Mathias
  full_name: Lechner, Mathias
  id: 3DC22916-F248-11E8-B48F-1D18A9856A87
  last_name: Lechner
- first_name: Thomas A
  full_name: Henzinger, Thomas A
  id: 40876CD8-F248-11E8-B48F-1D18A9856A87
  last_name: Henzinger
  orcid: 0000-0002-2985-7724
- first_name: Krishnendu
  full_name: Chatterjee, Krishnendu
  id: 2E5DCA20-F248-11E8-B48F-1D18A9856A87
  last_name: Chatterjee
  orcid: 0000-0002-4561-241X
citation:
  ama: 'Zikelic D, Lechner M, Henzinger TA, Chatterjee K. Learning control policies
    for stochastic systems with reach-avoid guarantees. In: <i>Proceedings of the
    37th AAAI Conference on Artificial Intelligence</i>. Vol 37. Association for the
    Advancement of Artificial Intelligence; 2023:11926-11935. doi:<a href="https://doi.org/10.1609/aaai.v37i10.26407">10.1609/aaai.v37i10.26407</a>'
  apa: 'Zikelic, D., Lechner, M., Henzinger, T. A., &#38; Chatterjee, K. (2023). Learning
    control policies for stochastic systems with reach-avoid guarantees. In <i>Proceedings
    of the 37th AAAI Conference on Artificial Intelligence</i> (Vol. 37, pp. 11926–11935).
    Washington, DC, United States: Association for the Advancement of Artificial Intelligence.
    <a href="https://doi.org/10.1609/aaai.v37i10.26407">https://doi.org/10.1609/aaai.v37i10.26407</a>'
  chicago: Zikelic, Dorde, Mathias Lechner, Thomas A Henzinger, and Krishnendu Chatterjee.
    “Learning Control Policies for Stochastic Systems with Reach-Avoid Guarantees.”
    In <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>,
    37:11926–35. Association for the Advancement of Artificial Intelligence, 2023.
    <a href="https://doi.org/10.1609/aaai.v37i10.26407">https://doi.org/10.1609/aaai.v37i10.26407</a>.
  ieee: D. Zikelic, M. Lechner, T. A. Henzinger, and K. Chatterjee, “Learning control
    policies for stochastic systems with reach-avoid guarantees,” in <i>Proceedings
    of the 37th AAAI Conference on Artificial Intelligence</i>, Washington, DC, United
    States, 2023, vol. 37, no. 10, pp. 11926–11935.
  ista: 'Zikelic D, Lechner M, Henzinger TA, Chatterjee K. 2023. Learning control
    policies for stochastic systems with reach-avoid guarantees. Proceedings of the
    37th AAAI Conference on Artificial Intelligence. AAAI: Conference on Artificial
    Intelligence vol. 37, 11926–11935.'
  mla: Zikelic, Dorde, et al. “Learning Control Policies for Stochastic Systems with
    Reach-Avoid Guarantees.” <i>Proceedings of the 37th AAAI Conference on Artificial
    Intelligence</i>, vol. 37, no. 10, Association for the Advancement of Artificial
    Intelligence, 2023, pp. 11926–35, doi:<a href="https://doi.org/10.1609/aaai.v37i10.26407">10.1609/aaai.v37i10.26407</a>.
  short: D. Zikelic, M. Lechner, T.A. Henzinger, K. Chatterjee, in:, Proceedings of
    the 37th AAAI Conference on Artificial Intelligence, Association for the Advancement
    of Artificial Intelligence, 2023, pp. 11926–11935.
conference:
  end_date: 2023-02-14
  location: Washington, DC, United States
  name: 'AAAI: Conference on Artificial Intelligence'
  start_date: 2023-02-07
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: <i>37th Conference
    on Neural Information Processing Systems</i>. ; 2023.'
  apa: Zikelic, D., Lechner, M., Verma, A., Chatterjee, K., &#38; Henzinger, T. A.
    (2023). Compositional policy learning in stochastic control systems with formal
    guarantees. In <i>37th Conference on Neural Information Processing Systems</i>.
    New Orleans, LO, United States.
  chicago: Zikelic, Dorde, Mathias Lechner, Abhinav Verma, Krishnendu Chatterjee,
    and Thomas A Henzinger. “Compositional Policy Learning in Stochastic Control Systems
    with Formal Guarantees.” In <i>37th Conference on Neural Information Processing
    Systems</i>, 2023.
  ieee: D. Zikelic, M. Lechner, A. Verma, K. Chatterjee, and T. A. Henzinger, “Compositional
    policy learning in stochastic control systems with formal guarantees,” in <i>37th
    Conference on Neural Information Processing Systems</i>, New Orleans, LO, United
    States, 2023.
  ista: 'Zikelic D, Lechner M, Verma A, Chatterjee K, Henzinger TA. 2023. Compositional
    policy learning in stochastic control systems with formal guarantees. 37th Conference
    on Neural Information Processing Systems. NeurIPS: Neural Information Processing
    Systems.'
  mla: Zikelic, Dorde, et al. “Compositional Policy Learning in Stochastic Control
    Systems with Formal Guarantees.” <i>37th Conference on Neural Information Processing
    Systems</i>, 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: <i>Tools
    and Algorithms for the Construction and Analysis of Systems </i>. Vol 13993. Springer
    Nature; 2023:3-25. doi:<a href="https://doi.org/10.1007/978-3-031-30823-9_1">10.1007/978-3-031-30823-9_1</a>'
  apa: 'Chatterjee, K., Henzinger, T. A., Lechner, M., &#38; Zikelic, D. (2023). A
    learner-verifier framework for neural network controllers and certificates of
    stochastic systems. In <i>Tools and Algorithms for the Construction and Analysis
    of Systems </i> (Vol. 13993, pp. 3–25). Paris, France: Springer Nature. <a href="https://doi.org/10.1007/978-3-031-30823-9_1">https://doi.org/10.1007/978-3-031-30823-9_1</a>'
  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 <i>Tools and Algorithms for the Construction and Analysis
    of Systems </i>, 13993:3–25. Springer Nature, 2023. <a href="https://doi.org/10.1007/978-3-031-30823-9_1">https://doi.org/10.1007/978-3-031-30823-9_1</a>.
  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 <i>Tools and Algorithms for the Construction and Analysis of Systems </i>,
    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.” <i>Tools and Algorithms for
    the Construction and Analysis of Systems </i>, vol. 13993, Springer Nature, 2023,
    pp. 3–25, doi:<a href="https://doi.org/10.1007/978-3-031-30823-9_1">10.1007/978-3-031-30823-9_1</a>.
  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: '13238'
abstract:
- lang: eng
  text: "We consider a natural problem dealing with weighted packet selection across
    a rechargeable link, which e.g., finds applications in cryptocurrency networks.
    The capacity of a link (u, v) is determined by how much nodes u and v allocate
    for this link. Specifically, the input is a finite ordered sequence of packets
    that arrive in both directions along a link. Given (u, v) and a packet of weight
    x going from u to v, node u can either accept or reject the packet. If u accepts
    the packet, the capacity on link (u, v) decreases by x. Correspondingly, v’s capacity
    on (u, v) increases by x. If a node rejects the packet, this will entail a cost
    affinely linear in the weight of the packet. A link is “rechargeable” in the sense
    that the total capacity of the link has to remain constant, but the allocation
    of capacity at the ends of the link can depend arbitrarily on the nodes’ decisions.
    The goal is to minimise the sum of the capacity injected into the link and the
    cost of rejecting packets. We show that the problem is NP-hard, but can be approximated
    efficiently with a ratio of (1+ε)⋅(1+3–√) for some arbitrary ε>0.\r\n."
acknowledgement: We thank Mahsa Bastankhah and Mohammad Ali Maddah-Ali for fruitful
  discussions about different variants of the problem. This work is supported by the
  European Research Council (ERC) Consolidator Project 864228 (AdjustNet), 2020-2025,
  the ERC CoG 863818 (ForM-SMArt), and the German Research Foundation (DFG) grant
  470029389 (FlexNets), 2021–2024.
alternative_title:
- LNCS
article_processing_charge: No
arxiv: 1
author:
- 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: 'Schmid S, Svoboda J, Yeo MX. Weighted packet selection for rechargeable links
    in cryptocurrency networks: Complexity and approximation. In: <i>SIROCCO 2023:
    Structural Information and Communication Complexity </i>. Vol 13892. Springer
    Nature; 2023:576-594. doi:<a href="https://doi.org/10.1007/978-3-031-32733-9_26">10.1007/978-3-031-32733-9_26</a>'
  apa: 'Schmid, S., Svoboda, J., &#38; Yeo, M. X. (2023). Weighted packet selection
    for rechargeable links in cryptocurrency networks: Complexity and approximation.
    In <i>SIROCCO 2023: Structural Information and Communication Complexity </i> (Vol.
    13892, pp. 576–594). Alcala de Henares, Spain: Springer Nature. <a href="https://doi.org/10.1007/978-3-031-32733-9_26">https://doi.org/10.1007/978-3-031-32733-9_26</a>'
  chicago: 'Schmid, Stefan, Jakub Svoboda, and Michelle X Yeo. “Weighted Packet Selection
    for Rechargeable Links in Cryptocurrency Networks: Complexity and Approximation.”
    In <i>SIROCCO 2023: Structural Information and Communication Complexity </i>,
    13892:576–94. Springer Nature, 2023. <a href="https://doi.org/10.1007/978-3-031-32733-9_26">https://doi.org/10.1007/978-3-031-32733-9_26</a>.'
  ieee: 'S. Schmid, J. Svoboda, and M. X. Yeo, “Weighted packet selection for rechargeable
    links in cryptocurrency networks: Complexity and approximation,” in <i>SIROCCO
    2023: Structural Information and Communication Complexity </i>, Alcala de Henares,
    Spain, 2023, vol. 13892, pp. 576–594.'
  ista: 'Schmid S, Svoboda J, Yeo MX. 2023. Weighted packet selection for rechargeable
    links in cryptocurrency networks: Complexity and approximation. SIROCCO 2023:
    Structural Information and Communication Complexity . SIROCCO: Structural Information
    and Communication Complexity, LNCS, vol. 13892, 576–594.'
  mla: 'Schmid, Stefan, et al. “Weighted Packet Selection for Rechargeable Links in Cryptocurrency
    Networks: Complexity and Approximation.” <i>SIROCCO 2023: Structural Information
    and Communication Complexity </i>, vol. 13892, Springer Nature, 2023, pp. 576–94,
    doi:<a href="https://doi.org/10.1007/978-3-031-32733-9_26">10.1007/978-3-031-32733-9_26</a>.'
  short: 'S. Schmid, J. Svoboda, M.X. Yeo, in:, SIROCCO 2023: Structural Information
    and Communication Complexity , Springer Nature, 2023, pp. 576–594.'
conference:
  end_date: 2023-06-09
  location: Alcala de Henares, Spain
  name: 'SIROCCO: Structural Information and Communication Complexity'
  start_date: 2023-06-06
date_created: 2023-07-16T22:01:12Z
date_published: 2023-05-25T00:00:00Z
date_updated: 2025-07-14T09:09:53Z
day: '25'
department:
- _id: KrPi
- _id: KrCh
doi: 10.1007/978-3-031-32733-9_26
ec_funded: 1
external_id:
  arxiv:
  - '2204.13459'
intvolume: '     13892'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.48550/arXiv.2204.13459
month: '05'
oa: 1
oa_version: Preprint
page: 576-594
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
publication: 'SIROCCO 2023: Structural Information and Communication Complexity '
publication_identifier:
  eissn:
  - 1611-3349
  isbn:
  - '9783031327322'
  issn:
  - 0302-9743
publication_status: published
publisher: Springer Nature
quality_controlled: '1'
related_material:
  record:
  - id: '14506'
    relation: dissertation_contains
    status: public
scopus_import: '1'
status: public
title: 'Weighted packet selection for rechargeable links in cryptocurrency networks:
  Complexity and approximation'
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 13892
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. <i>Nature Communications</i>.
    2023;14. doi:<a href="https://doi.org/10.1038/s41467-023-39625-9">10.1038/s41467-023-39625-9</a>
  apa: Kleshnina, M., Hilbe, C., Simsa, S., Chatterjee, K., &#38; Nowak, M. A. (2023).
    The effect of environmental information on evolution of cooperation in stochastic
    games. <i>Nature Communications</i>. Springer Nature. <a href="https://doi.org/10.1038/s41467-023-39625-9">https://doi.org/10.1038/s41467-023-39625-9</a>
  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.” <i>Nature Communications</i>. Springer Nature,
    2023. <a href="https://doi.org/10.1038/s41467-023-39625-9">https://doi.org/10.1038/s41467-023-39625-9</a>.
  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,”
    <i>Nature Communications</i>, 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.” <i>Nature Communications</i>, vol. 14, 4153,
    Springer Nature, 2023, doi:<a href="https://doi.org/10.1038/s41467-023-39625-9">10.1038/s41467-023-39625-9</a>.
  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: <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>.
    Vol 37. Association for the Advancement of Artificial Intelligence; 2023:14964-14973.
    doi:<a href="https://doi.org/10.1609/aaai.v37i12.26747">10.1609/aaai.v37i12.26747</a>'
  apa: 'Lechner, M., Zikelic, D., Chatterjee, K., Henzinger, T. A., &#38; Rus, D.
    (2023). Quantization-aware interval bound propagation for training certifiably
    robust quantized neural networks. In <i>Proceedings of the 37th AAAI Conference
    on Artificial Intelligence</i> (Vol. 37, pp. 14964–14973). Washington, DC, United
    States: Association for the Advancement of Artificial Intelligence. <a href="https://doi.org/10.1609/aaai.v37i12.26747">https://doi.org/10.1609/aaai.v37i12.26747</a>'
  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 <i>Proceedings of the 37th AAAI Conference
    on Artificial Intelligence</i>, 37:14964–73. Association for the Advancement of
    Artificial Intelligence, 2023. <a href="https://doi.org/10.1609/aaai.v37i12.26747">https://doi.org/10.1609/aaai.v37i12.26747</a>.
  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 <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>,
    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.” <i>Proceedings of the
    37th AAAI Conference on Artificial Intelligence</i>, vol. 37, no. 12, Association
    for the Advancement of Artificial Intelligence, 2023, pp. 14964–73, doi:<a href="https://doi.org/10.1609/aaai.v37i12.26747">10.1609/aaai.v37i12.26747</a>.
  short: M. Lechner, D. Zikelic, K. Chatterjee, T.A. Henzinger, D. Rus, in:, Proceedings
    of the 37th AAAI Conference on Artificial Intelligence, Association for the Advancement
    of Artificial Intelligence, 2023, pp. 14964–14973.
conference:
  end_date: 2023-02-14
  location: Washington, DC, United States
  name: 'AAAI: Conference on Artificial Intelligence'
  start_date: 2023-02-07
date_created: 2023-08-27T22:01:17Z
date_published: 2023-06-26T00:00:00Z
date_updated: 2025-07-14T09:09:56Z
day: '26'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v37i12.26747
ec_funded: 1
external_id:
  arxiv:
  - '2211.16187'
intvolume: '        37'
issue: '12'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.48550/arXiv.2211.16187
month: '06'
oa: 1
oa_version: Preprint
page: 14964-14973
project:
- _id: 62781420-2b32-11ec-9570-8d9b63373d4d
  call_identifier: H2020
  grant_number: '101020093'
  name: Vigilant Algorithmic Monitoring of Software
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication: Proceedings of the 37th AAAI Conference on Artificial Intelligence
publication_identifier:
  isbn:
  - '9781577358800'
publication_status: published
publisher: Association for the Advancement of Artificial Intelligence
quality_controlled: '1'
scopus_import: '1'
status: public
title: Quantization-aware interval bound propagation for training certifiably robust
  quantized neural networks
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2023'
...
---
_id: '14243'
abstract:
- lang: eng
  text: 'Two-player zero-sum "graph games" are central in logic, verification, and
    multi-agent systems. The game proceeds by placing a token on a vertex of a graph,
    and allowing the players to move it to produce an infinite path, which determines
    the winner or payoff of the game. Traditionally, the players alternate turns in
    moving the token. In "bidding games", however, the players have budgets and in
    each turn, an auction (bidding) determines which player moves the token. So far,
    bidding games have only been studied as full-information games. In this work we
    initiate the study of partial-information bidding games: we study bidding games
    in which a player''s initial budget is drawn from a known probability distribution.
    We show that while for some bidding mechanisms and objectives, it is straightforward
    to adapt the results from the full-information setting to the partial-information
    setting, for others, the analysis is significantly more challenging, requires
    new techniques, and gives rise to interesting results. Specifically, we study
    games with "mean-payoff" objectives in combination with "poorman" bidding. We
    construct optimal strategies for a partially-informed player who plays against
    a fully-informed adversary. We show that, somewhat surprisingly, the "value" under
    pure strategies does not necessarily exist in such games.'
acknowledgement: This research was supported in part by ISF grant no.1679/21, by the
  ERC CoG 863818 (ForM-SMArt), and the European Union’s Horizon 2020 research and
  innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 665385.
article_processing_charge: No
arxiv: 1
author:
- first_name: Guy
  full_name: Avni, Guy
  id: 463C8BC2-F248-11E8-B48F-1D18A9856A87
  last_name: Avni
  orcid: 0000-0001-5588-8287
- first_name: Ismael R
  full_name: Jecker, Ismael R
  id: 85D7C63E-7D5D-11E9-9C0F-98C4E5697425
  last_name: Jecker
- first_name: Dorde
  full_name: Zikelic, Dorde
  id: 294AA7A6-F248-11E8-B48F-1D18A9856A87
  last_name: Zikelic
  orcid: 0000-0002-4681-1699
citation:
  ama: 'Avni G, Jecker IR, Zikelic D. Bidding graph games with partially-observable
    budgets. In: <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>.
    Vol 37. ; 2023:5464-5471. doi:<a href="https://doi.org/10.1609/aaai.v37i5.25679">10.1609/aaai.v37i5.25679</a>'
  apa: Avni, G., Jecker, I. R., &#38; Zikelic, D. (2023). Bidding graph games with
    partially-observable budgets. In <i>Proceedings of the 37th AAAI Conference on
    Artificial Intelligence</i> (Vol. 37, pp. 5464–5471). Washington, DC, United States.
    <a href="https://doi.org/10.1609/aaai.v37i5.25679">https://doi.org/10.1609/aaai.v37i5.25679</a>
  chicago: Avni, Guy, Ismael R Jecker, and Dorde Zikelic. “Bidding Graph Games with
    Partially-Observable Budgets.” In <i>Proceedings of the 37th AAAI Conference on
    Artificial Intelligence</i>, 37:5464–71, 2023. <a href="https://doi.org/10.1609/aaai.v37i5.25679">https://doi.org/10.1609/aaai.v37i5.25679</a>.
  ieee: G. Avni, I. R. Jecker, and D. Zikelic, “Bidding graph games with partially-observable
    budgets,” in <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>,
    Washington, DC, United States, 2023, vol. 37, no. 5, pp. 5464–5471.
  ista: 'Avni G, Jecker IR, Zikelic D. 2023. Bidding graph games with partially-observable
    budgets. Proceedings of the 37th AAAI Conference on Artificial Intelligence. AAAI:
    Conference on Artificial Intelligence vol. 37, 5464–5471.'
  mla: Avni, Guy, et al. “Bidding Graph Games with Partially-Observable Budgets.”
    <i>Proceedings of the 37th AAAI Conference on Artificial Intelligence</i>, vol.
    37, no. 5, 2023, pp. 5464–71, doi:<a href="https://doi.org/10.1609/aaai.v37i5.25679">10.1609/aaai.v37i5.25679</a>.
  short: G. Avni, I.R. Jecker, D. Zikelic, in:, Proceedings of the 37th AAAI Conference
    on Artificial Intelligence, 2023, pp. 5464–5471.
conference:
  end_date: 2023-02-14
  location: Washington, DC, United States
  name: 'AAAI: Conference on Artificial Intelligence'
  start_date: 2023-02-07
date_created: 2023-08-27T22:01:18Z
date_published: 2023-06-27T00:00:00Z
date_updated: 2025-07-14T09:09:56Z
day: '27'
department:
- _id: ToHe
- _id: KrCh
doi: 10.1609/aaai.v37i5.25679
ec_funded: 1
external_id:
  arxiv:
  - '2211.13626'
intvolume: '        37'
issue: '5'
language:
- iso: eng
main_file_link:
- open_access: '1'
  url: https://doi.org/10.1609/aaai.v37i5.25679
month: '06'
oa: 1
oa_version: Published Version
page: 5464-5471
project:
- _id: 0599E47C-7A3F-11EA-A408-12923DDC885E
  call_identifier: H2020
  grant_number: '863818'
  name: 'Formal Methods for Stochastic Models: Algorithms and Applications'
- _id: 2564DBCA-B435-11E9-9278-68D0E5697425
  call_identifier: H2020
  grant_number: '665385'
  name: International IST Doctoral Program
publication: Proceedings of the 37th AAAI Conference on Artificial Intelligence
publication_identifier:
  isbn:
  - '9781577358800'
publication_status: published
quality_controlled: '1'
scopus_import: '1'
status: public
title: Bidding graph games with partially-observable budgets
type: conference
user_id: 2DF688A6-F248-11E8-B48F-1D18A9856A87
volume: 37
year: '2023'
...
---
_id: '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: <i>Proceedings of
    the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms</i>. Society for Industrial
    and Applied Mathematics; 2023:4590-4605. doi:<a href="https://doi.org/10.1137/1.9781611977554.ch173">10.1137/1.9781611977554.ch173</a>'
  apa: 'Chatterjee, K., Meggendorfer, T., Saona Urmeneta, R. J., &#38; Svoboda, J.
    (2023). Faster algorithm for turn-based stochastic games with bounded treewidth.
    In <i>Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms</i>
    (pp. 4590–4605). Florence, Italy: Society for Industrial and Applied Mathematics.
    <a href="https://doi.org/10.1137/1.9781611977554.ch173">https://doi.org/10.1137/1.9781611977554.ch173</a>'
  chicago: Chatterjee, Krishnendu, Tobias Meggendorfer, Raimundo J Saona Urmeneta,
    and Jakub Svoboda. “Faster Algorithm for Turn-Based Stochastic Games with Bounded
    Treewidth.” In <i>Proceedings of the 2023 Annual ACM-SIAM Symposium on Discrete
    Algorithms</i>, 4590–4605. Society for Industrial and Applied Mathematics, 2023.
    <a href="https://doi.org/10.1137/1.9781611977554.ch173">https://doi.org/10.1137/1.9781611977554.ch173</a>.
  ieee: K. Chatterjee, T. Meggendorfer, R. J. Saona Urmeneta, and J. Svoboda, “Faster
    algorithm for turn-based stochastic games with bounded treewidth,” in <i>Proceedings
    of the 2023 Annual ACM-SIAM Symposium on Discrete Algorithms</i>, 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.” <i>Proceedings of the 2023 Annual ACM-SIAM Symposium
    on Discrete Algorithms</i>, Society for Industrial and Applied Mathematics, 2023,
    pp. 4590–605, doi:<a href="https://doi.org/10.1137/1.9781611977554.ch173">10.1137/1.9781611977554.ch173</a>.
  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. <i>Formal Methods in System Design</i>. 2023. doi:<a
    href="https://doi.org/10.1007/s10703-023-00411-4">10.1007/s10703-023-00411-4</a>
  apa: Chatterjee, K., Katoen, J. P., Mohr, S., Weininger, M., &#38; Winkler, T. (2023).
    Stochastic games with lexicographic objectives. <i>Formal Methods in System Design</i>.
    Springer Nature. <a href="https://doi.org/10.1007/s10703-023-00411-4">https://doi.org/10.1007/s10703-023-00411-4</a>
  chicago: Chatterjee, Krishnendu, Joost P Katoen, Stefanie Mohr, Maximilian Weininger,
    and Tobias Winkler. “Stochastic Games with Lexicographic Objectives.” <i>Formal
    Methods in System Design</i>. Springer Nature, 2023. <a href="https://doi.org/10.1007/s10703-023-00411-4">https://doi.org/10.1007/s10703-023-00411-4</a>.
  ieee: K. Chatterjee, J. P. Katoen, S. Mohr, M. Weininger, and T. Winkler, “Stochastic
    games with lexicographic objectives,” <i>Formal Methods in System Design</i>.
    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.”
    <i>Formal Methods in System Design</i>, Springer Nature, 2023, doi:<a href="https://doi.org/10.1007/s10703-023-00411-4">10.1007/s10703-023-00411-4</a>.
  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. <i>Proceedings of the Royal Society
    A: Mathematical, Physical and Engineering Sciences</i>. 2023;479(2271). doi:<a
    href="https://doi.org/10.1098/rspa.2022.0685">10.1098/rspa.2022.0685</a>'
  apa: 'Svoboda, J., Tkadlec, J., Kaveh, K., &#38; Chatterjee, K. (2023). Coexistence
    times in the Moran process with environmental heterogeneity. <i>Proceedings of
    the Royal Society A: Mathematical, Physical and Engineering Sciences</i>. The
    Royal Society. <a href="https://doi.org/10.1098/rspa.2022.0685">https://doi.org/10.1098/rspa.2022.0685</a>'
  chicago: 'Svoboda, Jakub, Josef Tkadlec, Kamran Kaveh, and Krishnendu Chatterjee.
    “Coexistence Times in the Moran Process with Environmental Heterogeneity.” <i>Proceedings
    of the Royal Society A: Mathematical, Physical and Engineering Sciences</i>. The
    Royal Society, 2023. <a href="https://doi.org/10.1098/rspa.2022.0685">https://doi.org/10.1098/rspa.2022.0685</a>.'
  ieee: 'J. Svoboda, J. Tkadlec, K. Kaveh, and K. Chatterjee, “Coexistence times in
    the Moran process with environmental heterogeneity,” <i>Proceedings of the Royal
    Society A: Mathematical, Physical and Engineering Sciences</i>, 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.” <i>Proceedings of the Royal Society A: Mathematical, Physical
    and Engineering Sciences</i>, vol. 479, no. 2271, 20220685, The Royal Society,
    2023, doi:<a href="https://doi.org/10.1098/rspa.2022.0685">10.1098/rspa.2022.0685</a>.'
  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'
...
