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We consider a 3-player game in the normal form, in which each player has two actions. We assume that the game is symmetric and repeated infinitely many times. At each stage players make their choices knowing only the average payoffs from…

Optimization and Control · Mathematics 2018-05-16 Tadeusz Kufel , Sławomir Plaskacz , Joanna Zwierzchowska

In this paper we present a novel generic mapping between Graphical Games and Markov Random Fields so that pure Nash equilibria in the former can be found by statistical inference on the latter. Thus, the problem of deciding whether a…

Computer Science and Game Theory · Computer Science 2007-05-23 Constantinos Daskalakis

In this paper, we consider two-player zero-sum matrix and stochastic games and develop learning dynamics that are payoff-based, convergent, rational, and symmetric between the two players. Specifically, the learning dynamics for matrix…

Machine Learning · Computer Science 2024-09-06 Zaiwei Chen , Kaiqing Zhang , Eric Mazumdar , Asuman Ozdaglar , Adam Wierman

Synthesis of finite-state controllers from high-level specifications in multi-agent systems can be reduced to solving multi-player concurrent games over finite graphs. The complexity of solving such games with qualitative objectives for…

Computer Science and Game Theory · Computer Science 2018-09-28 Shaull Almagor , Rajeev Alur , Suguman Bansal

In this article, we consider generalized Nash games where the associated constraint map is not necessarily self. The classical Nash equilibrium may not exist for such games and therefore we introduce the notion of best approximate solution…

Optimization and Control · Mathematics 2022-04-05 Asrifa Sultana , Shivani Valecha

In this paper we establish a new connection between a class of 2-player nonzero-sum games of optimal stopping and certain $2$-player nonzero-sum games of singular control. We show that whenever a Nash equilibrium in the game of stopping is…

Optimization and Control · Mathematics 2017-12-29 Tiziano De Angelis , Giorgio Ferrari

A recent body of experimental literature has studied empirical game-theoretical analysis, in which we have partial knowledge of a game, consisting of observations of a subset of the pure-strategy profiles and their associated payoffs to…

Computer Science and Game Theory · Computer Science 2014-02-13 John Fearnley , Martin Gairing , Paul Goldberg , Rahul Savani

We consider the question of whether, and in what sense, Wardrop equilibria provide a good approximation for Nash equilibria in atomic unsplittable congestion games with a large number of small players. We examine two different definitions…

Computer Science and Game Theory · Computer Science 2022-05-03 Roberto Cominetti , Marco Scarsini , Marc Schröder , Nicolás Stier-Moses

We analyze best response dynamics for finding a Nash equilibrium of an infinite horizon zero-sum stochastic linear quadratic dynamic game (LQDG) with partial and asymmetric information. We derive explicit expressions for each player's best…

Systems and Control · Electrical Eng. & Systems 2025-09-03 Yuxiang Guan , Iman Shames , Tyler H. Summers

A strategy profile in a multi-player game is a Nash equilibrium if no player can unilaterally deviate to achieve a strictly better payoff. A profile is an $\epsilon$-Nash equilibrium if no player can gain more than $\epsilon$ by…

Computer Science and Game Theory · Computer Science 2026-01-27 Ali Asadi , Léonard Brice , Krishnendu Chatterjee , K. S. Thejaswini

We investigate the problem of equilibrium computation for "large" $n$-player games. Large games have a Lipschitz-type property that no single player's utility is greatly affected by any other individual player's actions. In this paper, we…

Computer Science and Game Theory · Computer Science 2016-10-28 Paul W. Goldberg , Francisco J. Marmolejo-Cossío , Zhiwei Steven Wu

It is known that there are uncoupled learning heuristics leading to Nash equilibrium in all finite games. Why should players use such learning heuristics and where could they come from? We show that there is no uncoupled learning heuristic…

Computer Science and Game Theory · Computer Science 2015-04-27 Burkhard C. Schipper

This paper shows the existence of $\mathcal{O}(\frac{1}{n^\gamma})$-Nash equilibria in $n$-player noncooperative sum-aggregative games in which the players' cost functions, depending only on their own action and the average of all players'…

Optimization and Control · Mathematics 2022-09-27 Kang Liu , Nadia Oudjane , Cheng Wan

We propose a general class of symmetric games called position-optimization games. Given a probability distribution $Q$ over a set of targets $\mathcal{Y}$, the $n$ players each choose a position in a space $\mathcal{X}$. A player's utility…

Computer Science and Game Theory · Computer Science 2026-02-18 Rafael Frongillo , Melody Hsu , Mary Monroe , Anish Thilagar

In this paper we consider strong Nash equilibria, in mixed strategies, for finite games. Any strong Nash equilibrium outcome is Pareto efficient for each coalition. First, we analyze the two--player setting. Our main result, in its simplest…

Optimization and Control · Mathematics 2015-03-02 Eleonora Braggion , Nicola Gatti , Roberto Lucchetti , Tuomas Sandholm

The standard game-theoretic solution concept, Nash equilibrium, assumes that all players behave rationally. If we follow a Nash equilibrium and opponents are irrational (or follow strategies from a different Nash equilibrium), then we may…

Computer Science and Game Theory · Computer Science 2023-08-22 Sam Ganzfried

We study the computation of equilibria of anonymous games, via algorithms that may proceed via a sequence of adaptive queries to the game's payoff function, assumed to be unknown initially. The general topic we consider is \emph{query…

Computer Science and Game Theory · Computer Science 2016-05-06 Paul W. Goldberg , Stefano Turchetta

We investigate the convergence of symmetric stochastic differential games with interactions via control, where the volatility terms of both idiosyncratic and common noises are controlled. We apply the stochastic maximum principle, following…

Probability · Mathematics 2026-02-19 Erhan Bayraktar , Hiroaki Horikawa

Contemporary applications of machine learning in two-team e-sports and the superior expressivity of multi-agent generative adversarial networks raise important and overlooked theoretical questions regarding optimization in two-team games.…

Computer Science and Game Theory · Computer Science 2023-04-18 Fivos Kalogiannis , Ioannis Panageas , Emmanouil-Vasileios Vlatakis-Gkaragkounis

In an $\epsilon$-Nash equilibrium, a player can gain at most $\epsilon$ by unilaterally changing his behaviour. For two-player (bimatrix) games with payoffs in $[0,1]$, the best-known$\epsilon$ achievable in polynomial time is 0.3393. In…

Computer Science and Game Theory · Computer Science 2014-10-02 Argyrios Deligkas , John Fearnley , Rahul Savani , Paul Spirakis
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