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In an epsilon-Nash equilibrium, a player can gain at most epsilon by changing his behaviour. Recent work has addressed the question of how best to compute epsilon-Nash equilibria, and for what values of epsilon a polynomial-time algorithm…

Computer Science and Game Theory · Computer Science 2015-03-20 John Fearnley , Paul W. Goldberg , Rahul Savani , Troels Bjerre Sørensen

Over the years, researchers have studied the complexity of several decision versions of Nash equilibrium in (symmetric) two-player games (bimatrix games). To the best of our knowledge, the last remaining open problem of this sort is the…

Computer Science and Game Theory · Computer Science 2014-12-03 Ruta Mehta , Vijay V. Vazirani , Sadra Yazdanbod

We propose a framework to compute approximate Nash equilibria in integer programming games with nonlinear payoffs, i.e., simultaneous and non-cooperative games where each player solves a parametrized mixed-integer nonlinear program. We…

Optimization and Control · Mathematics 2025-08-04 Aloïs Duguet , Margarida Carvalho , Gabriele Dragotto , Sandra Ulrich Ngueveu

This work proposes a novel set of techniques for approximating a Nash equilibrium in a finite, normal-form game. It achieves this by constructing a new reformulation as solving a parameterized system of multivariate polynomials with tunable…

Computer Science and Game Theory · Computer Science 2024-11-05 Ian Gemp

A Nash Equilibrium (NE) is a strategy profile resilient to unilateral deviations, and is predominantly used in the analysis of multiagent systems. A downside of NE is that it is not necessarily stable against deviations by coalitions. Yet,…

Computer Science and Game Theory · Computer Science 2014-01-16 Michal Feldman , Tami Tamir

Wide machine learning tasks can be formulated as non-convex multi-player games, where Nash equilibrium (NE) is an acceptable solution to all players, since no one can benefit from changing its strategy unilaterally. Attributed to the…

Computer Science and Game Theory · Computer Science 2023-01-20 Guanpu Chen , Gehui Xu , Fengxiang He , Yiguang Hong , Leszek Rutkowski , Dacheng Tao

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

We conjecture that PPAD has a PCP-like complete problem, seeking a near equilibrium in which all but very few players have very little incentive to deviate. We show that, if one assumes that this problem requires exponential time, several…

Computational Complexity · Computer Science 2025-09-08 Yakov Babichenko , Christos Papadimitriou , Aviad Rubinstein

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

Many emerging applications - such as adversarial training, AI alignment, and robust optimization - can be framed as zero-sum games between neural nets, with von Neumann-Nash equilibria (NE) capturing the desirable system behavior. While…

Machine Learning · Computer Science 2025-12-02 Deep Patel , Emmanouil-Vasileios Vlatakis-Gkaragkounis

We explore the power of semidefinite programming (SDP) for finding additive $epsilon$-approximate Nash equilibria in bimatrix games. We introduce an SDP relaxation for a quadratic programming formulation of the Nash equilibrium (NE) problem…

Optimization and Control · Mathematics 2019-08-16 Amir Ali Ahmadi , Jeffrey Zhang

We prove that finding an $\epsilon$-approximate Nash equilibrium is PPAD-complete for constant $\epsilon$ and a particularly simple class of games: polymatrix, degree 3 graphical games, in which each player has only two actions. As…

Computer Science and Game Theory · Computer Science 2016-09-14 Aviad Rubinstein

We study the deterministic and randomized query complexity of finding approximate equilibria in bimatrix games. We show that the deterministic query complexity of finding an $\epsilon$-Nash equilibrium when $\epsilon < \frac{1}{2}$ is…

Computer Science and Game Theory · Computer Science 2014-02-13 John Fearnley , Rahul Savani

We prove that there exists a constant $\epsilon>0$ such that, assuming the Exponential Time Hypothesis for PPAD, computing an $\epsilon$-approximate Nash equilibrium in a two-player (nXn) game requires quasi-polynomial time,…

Computational Complexity · Computer Science 2016-08-31 Aviad Rubinstein

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 provide an in-depth study of Nash equilibria in multi-objective normal form games (MONFGs), i.e., normal form games with vectorial payoffs. Taking a utility-based approach, we assume that each player's utility can be modelled with a…

Computer Science and Game Theory · Computer Science 2022-07-19 Willem Röpke , Diederik M. Roijers , Ann Nowé , Roxana Rădulescu

In recent work of Hazan and Krauthgamer (SICOMP 2011), it was shown that finding an $\eps$-approximate Nash equilibrium with near-optimal value in a two-player game is as hard as finding a hidden clique of size $O(\log n)$ in the random…

Computational Complexity · Computer Science 2011-04-20 Per Austrin , Mark Braverman , Eden Chlamtac

We study the problem of repeated play in a zero-sum game in which the payoff matrix may change, in a possibly adversarial fashion, on each round; we call these Online Matrix Games. Finding the Nash Equilibrium (NE) of a two player zero-sum…

Machine Learning · Computer Science 2020-04-06 Adrian Rivera Cardoso , Jacob Abernethy , He Wang , Huan Xu

In this paper we consider the problem of computing an $\epsilon$-approximate Nash Equilibrium of a zero-sum game in a payoff matrix $A \in \mathbb{R}^{m \times n}$ with $O(1)$-bounded entries given access to a matrix-vector product oracle…

Optimization and Control · Mathematics 2025-09-05 Ishani Karmarkar , Liam O'Carroll , Aaron Sidford

This paper addresses the problem of learning a Nash equilibrium in $\gamma$-discounted multiplayer general-sum Markov Games (MG). A key component of this model is the possibility for the players to either collaborate or team apart to…

Computer Science and Game Theory · Computer Science 2017-03-07 Julien Pérolat , Florian Strub , Bilal Piot , Olivier Pietquin