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Related papers: Approximate Nash Equilibria via Sampling

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This paper addresses the problem of fair equilibrium selection in graphical games. Our approach is based on the data structure called the {\em best response policy}, which was proposed by Kearns et al. \cite{kls} as a way to represent all…

Computer Science and Game Theory · Computer Science 2007-05-23 Edith Elkind , Leslie Ann Goldberg , Paul W. Goldberg

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

Many efficient algorithms have been designed to recover Nash equilibria of various classes of finite games. Special classes of continuous games with infinite strategy spaces, such as polynomial games, can be solved by semidefinite…

Computer Science and Game Theory · Computer Science 2020-10-01 Lukáš Adam , Rostislav Horčík , Tomáš Kasl , Tomáš Kroupa

We study stochastic mean-field games among finite number of teams with large finite as well as infinite number of decision makers. For this class of games within static and dynamic settings, we establish the existence of a Nash equilibrium,…

Optimization and Control · Mathematics 2022-11-11 Sina Sanjari , Naci Saldi , Serdar Yüksel

Motivated by empirical evidence that individuals within group decision making simultaneously aspire to maximize utility and avoid inequality we propose a criterion based on the entropy-norm pair for geometric selection of strict Nash…

Physics and Society · Physics 2020-03-23 A. B. Leoneti , G. A. Prataviera

We consider multi-agent decision making where each agent optimizes its convex cost function subject to individual and coupling constraints. The constraint sets are compact convex subsets of a Euclidean space. To learn Nash equilibria, we…

Optimization and Control · Mathematics 2018-10-16 Tatiana Tatarenko , Maryam Kamgarpour

AI in Math deals with mathematics in a constructive manner so that reasoning becomes automated, less laborious, and less error-prone. For algorithms, the question becomes how to automate analyses for specific problems. For the first time,…

Computer Science and Game Theory · Computer Science 2023-10-13 Xiaotie Deng , Dongchen Li , Hanyu Li

We consider a weighted Shapley network design game, where selfish players choose paths in a network to minimize their cost. The cost function of each edge in the network is affine linear with respect to the sum of weights of the players who…

Computer Science and Game Theory · Computer Science 2023-12-19 Hangxin Gan , Xianhao Meng , Chunying Ren , Yongtang Shi

This paper provides theoretical bounds for empirical game theoretical analysis of complex multi-agent interactions. We provide insights in the empirical meta game showing that a Nash equilibrium of the meta-game is an approximate Nash…

Computer Science and Game Theory · Computer Science 2018-03-20 Karl Tuyls , Julien Perolat , Marc Lanctot , Joel Z Leibo , Thore Graepel

We present an algorithm that computes approximate pure Nash equilibria in a broad class of constraint satisfaction games that generalize the well-known cut and party affiliation games. Our results improve previous ones by Bhalgat et al.~(EC…

Computer Science and Game Theory · Computer Science 2014-02-17 Ioannis Caragiannis , Angelo Fanelli , Nick Gravin

We consider the class of two-person ordinal potential games where each player has the same number of actions $K$. Each game in this class admits at least one pure Nash equilibrium and the best-response dynamics converges to one of these…

Computer Science and Game Theory · Computer Science 2025-02-12 Andrea Collevecchio , Hlafo Alfie Mimun , Matteo Quattropani , Marco Scarsini

We propose the first loss function for approximate Nash equilibria of normal-form games that is amenable to unbiased Monte Carlo estimation. This construction allows us to deploy standard non-convex stochastic optimization techniques for…

Computer Science and Game Theory · Computer Science 2024-04-16 Ian Gemp , Luke Marris , Georgios Piliouras

In game theory, the concept of Nash equilibrium reflects the collective stability of some individual strategies chosen by selfish agents. The concept pertains to different classes of games, e.g. the sequential games, where the agents play…

Logic · Mathematics 2015-07-01 Stephane Le Roux

In this paper, the problem of finding a generalized Nash equilibrium (GNE) of a networked game is studied. Players are only able to choose their decisions from a feasible action set. The feasible set is considered to be a private linear…

Computer Science and Game Theory · Computer Science 2017-03-27 Farzad Salehisadaghiani , Lacra Pavel

We study a multi-leader single-follower congestion game where multiple users (leaders) choose one resource out of a set of resources and, after observing the realized loads, an adversary (single-follower) attacks the resources with maximum…

Computer Science and Game Theory · Computer Science 2021-12-15 Tobias Harks , Mona Henle , Max Klimm , Jannik Matuschke , Anja Schedel

We consider zero-sum repeated games in which the players are restricted to strategies that require only a limited amount of randomness. Let $v_n$ be the max-min value of the $n$ stage game; previous works have characterized…

Computer Science and Game Theory · Computer Science 2019-02-12 Mehrdad Valizadeh , Amin Gohari

Nash equilibrium serves as a fundamental mathematical tool in economics and game theory. However, it classically assumes knowledge of player utilities, whereas economics generally regards preferences as more fundamental. To leverage…

Computer Science and Game Theory · Computer Science 2026-05-11 Ian Gemp , Crystal Qian , Marc Lanctot , Kate Larson

Nash equilibrium is perhaps the best-known solution concept in game theory. Such a solution assigns a strategy to each player which offers no incentive to unilaterally deviate. While a Nash equilibrium is guaranteed to always exist, the…

Computer Science and Game Theory · Computer Science 2025-04-29 David Sychrovský , Christopher Solinas , Revan MacQueen , Kevin Wang , James R. Wright , Nathan R. Sturtevant , Michael Bowling

Decoding how rational agents should behave in shared systems remains a critical challenge within theoretical computer science, artificial intelligence and economics studies. Central to this challenge is the task of computing the solution…

Computer Science and Game Theory · Computer Science 2025-01-07 Dongge Wang , Xiang Yan , Zehao Dou , Wenhan Huang , Yaodong Yang , Xiaotie Deng

Data-driven modeling increasingly requires to find a Nash equilibrium in multi-player games, e.g. when training GANs. In this paper, we analyse a new extra-gradient method for Nash equilibrium finding, that performs gradient extrapolations…