3 Search Results for "Mousseau, Vincent"

Document
DOI: 10.4230/LIPIcs.SAT.2025.19
An Application of SAT Solvers in Integer Programming Games

Authors: Pravesh Koirala, Aditya Shrey, and Forrest Laine

Published in: LIPIcs, Volume 341, 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)

Abstract
Integer programming games (IPGs) are a popular game-theoretic tool to model an array of games where each player has a discrete strategy set. These games arise in important domains such as economics, transportation, cybersecurity, etc., but solving them is non-trivial as it is known that checking for the existence of pure Nash equilibria in an IPG is Σ₂^p-complete. Recent works have proposed a class of relaxed solution concepts for IPGs called locally optimal integer solutions (LOIS) and shown it to be an efficient alternative for pure Nash equilibria. While LOIS are significantly simpler to compute, they still do not scale when solved using traditional mathematical solvers, especially when high-quality solutions are desired. In this paper, we apply commercially available SAT solvers to find LOIS in IPGs. We investigate efficient encodings for a cybersecurity game and compare solution times when using SAT solvers vs mathematical program solvers. We also investigate the application of SAT solvers in graph games using a graph interdiction example and compare against the obtained LOI solutions against existing heuristics-based solutions. Our results indicate that with appropriate encodings, large-scale IPGs can be solved much more efficiently using SAT solvers. We also show that SAT solvers can be applied to graph games in conjunction with LOIS for obtaining high-quality solutions. Our results emphasize the potential of SAT solvers combined with LOIS to solve significant game theory problems.
Cite as

Pravesh Koirala, Aditya Shrey, and Forrest Laine. An Application of SAT Solvers in Integer Programming Games. In 28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 341, pp. 19:1-19:12, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{koirala_et_al:LIPIcs.SAT.2025.19,
  author =	{Koirala, Pravesh and Shrey, Aditya and Laine, Forrest},
  title =	{{An Application of SAT Solvers in Integer Programming Games}},
  booktitle =	{28th International Conference on Theory and Applications of Satisfiability Testing (SAT 2025)},
  pages =	{19:1--19:12},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-381-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{341},
  editor =	{Berg, Jeremias and Nordstr\"{o}m, Jakob},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.SAT.2025.19},
  URN =		{urn:nbn:de:0030-drops-237534},
  doi =		{10.4230/LIPIcs.SAT.2025.19},
  annote =	{Keywords: Game Theory, Integer Programming Games, SAT Solvers, Local Solutions, Graph Games}
}
Document
DOI: 10.4230/DagSemProc.09041.6
09041 Working Group on MCDM for Robust Multiobjective Optimization (1st Round)

Authors: Jos Figueira, Martin Geiger, Salvatore Greco, Johannes Jahn, Kathrin Klamroth, Masahiro Inuiguchi, Vincent Mousseau, Sayin Serpil, Roman Slowinski, Margaret M. Wiecek, and Witting Katrin

Published in: Dagstuhl Seminar Proceedings, Volume 9041, Hybrid and Robust Approaches to Multiobjective Optimization (2009)

Abstract
This group explored MCDM techniques for robust multiobjective optimization.
Cite as

Jos Figueira, Martin Geiger, Salvatore Greco, Johannes Jahn, Kathrin Klamroth, Masahiro Inuiguchi, Vincent Mousseau, Sayin Serpil, Roman Slowinski, Margaret M. Wiecek, and Witting Katrin. 09041 Working Group on MCDM for Robust Multiobjective Optimization (1st Round). In Hybrid and Robust Approaches to Multiobjective Optimization. Dagstuhl Seminar Proceedings, Volume 9041, pp. 1-2, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2009)

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@InProceedings{figueira_et_al:DagSemProc.09041.6,
  author =	{Figueira, Jos and Geiger, Martin and Greco, Salvatore and Jahn, Johannes and Klamroth, Kathrin and Inuiguchi, Masahiro and Mousseau, Vincent and Sayin Serpil and Slowinski, Roman and Wiecek, Margaret M. and Witting Katrin},
  title =	{{09041 Working Group on MCDM for Robust Multiobjective Optimization (1st Round)}},
  booktitle =	{Hybrid and Robust Approaches to Multiobjective Optimization},
  pages =	{1--2},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2009},
  volume =	{9041},
  editor =	{Kalyanmoy Deb and Salvatore Greco and Kaisa Miettinen and Eckart Zitzler},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.09041.6},
  URN =		{urn:nbn:de:0030-drops-20025},
  doi =		{10.4230/DagSemProc.09041.6},
  annote =	{Keywords: Robust multiobjective optimization}
}
Document
DOI: 10.4230/DagSemProc.04461.12
Multi-criteria ranking of a finite set of alternatives using ordinal regression and additive utility functions - a new UTA-GMS method

Authors: Roman Slowinski, Salvatore Greco, and Vincent Mousseau

Published in: Dagstuhl Seminar Proceedings, Volume 4461, Practical Approaches to Multi-Objective Optimization (2005)

Abstract
UTA-GMS is a new method for assessment of strong or weak outranking relation in a problem of multi-criteria ranking, proposed by the authors. The ranking concerns a finite but relatively large set of alternatives A. We assume indirect preference information supplied by the decision maker (DM) in form of a complete preorder on a subset of reference alternatives R, called reference preorder. The preference model build from this information is an additive value function. The technique of passing from reference preorder to compatible additive value functions is called ordinal regression and it is well known from the UTA method proposed by Jacquet-Lagreze and Siskos in 1982. Unlike in the UTA method, we take into account all compatible value functions (instead of one or several most characteristic) at the stage of ranking the whole set A of alternatives. Moreover, we do not impose the additive value function to have piecewise-linear components but we accept any additive form. The resulting relations in A are twofold: strong outranking (if alternative x has greater value than y for all compatible value functions) and weak outranking (if alternative x has greater value than y for at least one compatible value function). Strong outranking is a partial preorder and weak outranking is a complete preorder in A. The strong outranking is of particular interest for the DM – it corresponds to dominance relation when the set of reference alternatives is empty, and to a complete preorder relation when the reference ranking is compatible with a single value function only. This approach has several interesting extensions useful for practical applications. The method has been implemented for a PC and will be presented together with an example of application.
Cite as

Roman Slowinski, Salvatore Greco, and Vincent Mousseau. Multi-criteria ranking of a finite set of alternatives using ordinal regression and additive utility functions - a new UTA-GMS method. In Practical Approaches to Multi-Objective Optimization. Dagstuhl Seminar Proceedings, Volume 4461, pp. 1-4, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2005)

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@InProceedings{slowinski_et_al:DagSemProc.04461.12,
  author =	{Slowinski, Roman and Greco, Salvatore and Mousseau, Vincent},
  title =	{{Multi-criteria ranking of a finite set of alternatives using ordinal regression and additive utility functions - a new UTA-GMS method}},
  booktitle =	{Practical Approaches to Multi-Objective Optimization},
  pages =	{1--4},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2005},
  volume =	{4461},
  editor =	{J\"{u}rgen Branke and Kalyanmoy Deb and Kaisa Miettinen and Ralph E. Steuer},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.04461.12},
  URN =		{urn:nbn:de:0030-drops-2476},
  doi =		{10.4230/DagSemProc.04461.12},
  annote =	{Keywords: Multiple-criteria ranking, ordinal regression, partial preorder, UTA-like method}
}
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