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In this paper, we consider zero-sum repeated games in which the maximizer is restricted to strategies requiring no more than a limited amount of randomness. Particularly, we analyze the maxmin payoff of the maximizer in two models: the…

Information Theory · Computer Science 2018-10-11 Mehrdad Valizadeh , Amin Gohari

Exploiting the algebraic structure of the set of bimatrix games, a divide-and-conquer algorithm for finding Nash equilibria is proposed. The algorithm is fixed-parameter tractable with the size of the largest irreducible component of a game…

Computer Science and Game Theory · Computer Science 2014-04-04 Xiang Jiang , Arno Pauly

A classic model to study strategic decision making in multi-agent systems is the normal-form game. This model can be generalised to allow for an infinite number of pure strategies leading to continuous games. Multi-objective normal-form…

Computer Science and Game Theory · Computer Science 2023-03-02 Willem Röpke , Carla Groenland , Roxana Rădulescu , Ann Nowé , Diederik M. Roijers

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

One key in real-life Nash equilibrium applications is to calibrate players' cost functions. To leverage the approximation ability of neural networks, we proposed a general framework for optimizing and learning Nash equilibrium using neural…

Computer Science and Game Theory · Computer Science 2024-09-04 Di Zhang , Wei Gu , Qing Jin

This paper is about computing constrained approximate Nash equilibria in polymatrix games, which are succinctly represented many-player games defined by an interaction graph between the players. In a recent breakthrough, Rubinstein showed…

Computer Science and Game Theory · Computer Science 2017-05-09 Argyrios Deligkas , John Fearnley , Rahul Savani

We study the problem of checking for the existence of constrained pure Nash equilibria in a subclass of polymatrix games defined on weighted directed graphs. The payoff of a player is defined as the sum of nonnegative rational weights on…

Computer Science and Game Theory · Computer Science 2016-11-30 Sunil Simon , Dominik Wojtczak

To verify the robustness of a program or protocol, it is common in the computer science community to rely on the theoretical framework of game theory. In particular, if one seeks to enforce a desired property, or specification, despite an…

Computer Science and Game Theory · Computer Science 2026-05-20 Léonard Brice

In this paper, we study nonzero-sum separable games, which are continuous games whose payoffs take a sum-of-products form. Included in this subclass are all finite games and polynomial games. We investigate the structure of equilibria in…

Computer Science and Game Theory · Computer Science 2010-04-26 Noah D. Stein , Asuman Ozdaglar , Pablo A. Parrilo

Noncooperative games with uncertain payoffs have been classically studied under the expected-utility theory framework, which relies on the strong assumption that agents behave rationally. However, simple experiments on human decision makers…

Computer Science and Game Theory · Computer Science 2025-08-14 Ashok Krishnan K. S. , Hélène Le Cadre , Ana Bušić

Nash equilibrium is a central concept in game theory. Several Nash solvers exist, yet none scale to normal-form games with many actions and many players, especially those with payoff tensors too big to be stored in memory. In this work, we…

Computer Science and Game Theory · Computer Science 2022-02-07 Ian Gemp , Rahul Savani , Marc Lanctot , Yoram Bachrach , Thomas Anthony , Richard Everett , Andrea Tacchetti , Tom Eccles , János Kramár

This paper examines the convergence of no-regret learning in games with continuous action sets. For concreteness, we focus on learning via "dual averaging", a widely used class of no-regret learning schemes where players take small steps…

Optimization and Control · Mathematics 2018-01-17 Panayotis Mertikopoulos , Zhengyuan Zhou

We study a multi-agent decision problem in population games, where agents select from multiple available strategies and continually revise their selections based on the payoffs associated with these strategies. Unlike conventional…

Multiagent Systems · Computer Science 2024-09-17 Shinkyu Park

Estimating the unknown reward functions driving agents' behaviors is of central interest in inverse reinforcement learning and game theory. To tackle this problem, we develop a unified framework for reward function recovery in two-player…

Machine Learning · Computer Science 2026-05-20 Junyi Liao , Zihan Zhu , Ethan Fang , Zhuoran Yang , Vahid Tarokh

We study the computational complexity of solving stochastic games with mean-payoff objectives. Instead of identifying special classes in which simple strategies are sufficient to play $\epsilon$-optimally, or form $\epsilon$-Nash…

Computer Science and Game Theory · Computer Science 2024-05-16 Sougata Bose , Rasmus Ibsen-Jensen , Patrick Totzke

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

Exploiting the algebraic structure of the set of bimatrix games, a divide-and-conquer algorithm for finding Nash equilibria is proposed. The algorithm is fixed-parameter tractable with the size of the largest irreducible component of a game…

Computer Science and Game Theory · Computer Science 2013-01-01 Xiang Jiang , Arno Pauly

We consider a variant of the hide-and-seek game in which a seeker inspects multiple hiding locations to find multiple items hidden by a hider. Each hiding location has a maximum hiding capacity and a probability of detecting its hidden…

Computer Science and Game Theory · Computer Science 2024-06-26 Bastián Bahamondes , Mathieu Dahan

This paper studies a class of network games with linear-quadratic payoffs and externalities exerted through a strictly concave interaction function. This class of game is motivated by the diminishing marginal effects with peer influences.…

Optimization and Control · Mathematics 2024-06-04 Jiamin Cai , Chenyue Zhang , Hoi-To Wai

In this paper, we study the problem of learning the set of pure strategy Nash equilibria and the exact structure of a continuous-action graphical game with quadratic payoffs by observing a small set of perturbed equilibria. A…

Computer Science and Game Theory · Computer Science 2019-11-12 Adarsh Barik , Jean Honorio