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Nash Equilibrium (NE) is the canonical solution concept of game theory, which provides an elegant tool to understand the rationalities. Though mixed strategy NE exists in any game with finite players and actions, computing NE in two- or…

Computer Science and Game Theory · Computer Science 2024-05-07 Xinrun Wang , Chang Yang , Shuxin Li , Pengdeng Li , Xiao Huang , Hau Chan , Bo An

In this paper, we examine the Nash equilibrium convergence properties of no-regret learning in general N-player games. For concreteness, we focus on the archetypal follow the regularized leader (FTRL) family of algorithms, and we consider…

Computer Science and Game Theory · Computer Science 2021-02-05 Angeliki Giannou , Emmanouil-Vasileios Vlatakis-Gkaragkounis , Panayotis Mertikopoulos

In this paper, we introduce a framework of new mathematical representation of Game Theory, including static classical game and static quantum game. The idea is to find a set of base vectors in every single-player strategy space and to…

Quantum Physics · Physics 2007-05-23 Jinshan Wu

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

In this paper, we introduce several types of correspondences: weakly naturally quasiconvex, *-weakly naturally quasiconvex, weakly biconvex and correspondences with *--weakly convex graph and we prove some fixed point theorems for these…

Optimization and Control · Mathematics 2013-04-03 Monica Patriche

We define solution concepts appropriate for computationally bounded players playing a fixed finite game. To do so, we need to define what it means for a \emph{computational game}, which is a sequence of games that get larger in some…

Computer Science and Game Theory · Computer Science 2015-06-10 Joseph Y. Halpern , Rafael Pass , Lior Seeman

Nash Learning from Human Feedback is a game-theoretic framework for aligning large language models (LLMs) with human preferences by modeling learning as a two-player zero-sum game. However, using raw preference as the payoff in the game…

Computer Science and Game Theory · Computer Science 2025-05-28 Zhekun Shi , Kaizhao Liu , Qi Long , Weijie J. Su , Jiancong Xiao

We consider a general nonzero-sum impulse game with two players. The main mathematical contribution of the paper is a verification theorem which provides, under some regularity conditions, a suitable system of quasi-variational inequalities…

Probability · Mathematics 2018-11-09 René Aïd , Matteo Basei , Giorgia Callegaro , Luciano Campi , Tiziano Vargiolu

In this note, we study a class of deterministic finite-horizon linear-quadratic difference games with coupled affine inequality constraints involving both state and control variables. We show that the necessary conditions for the existence…

Optimization and Control · Mathematics 2025-10-06 Partha Sarathi Mohapatra , Puduru Viswanadha Reddy

Contrary to the customary view that the celebrated Nash-equilibrium theorem in Game Theory is paradigmatic for non-cooperative games, it is shown that, in fact, it is essentially based on a particularly strong cooperation assumption.…

Optimization and Control · Mathematics 2007-05-23 Elemer E Rosinger

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

We extend the study of the complexity of finding an $\eps$-approximate Nash equilibrium in congestion games from the case of positive delay functions to delays of arbitrary sign. We first prove that in symmetric games with $\alpha$-bounded…

Computer Science and Game Theory · Computer Science 2011-02-08 Frederic Magniez , Michel de Rougemont , Miklos Santha , Xavier Zeitoun

We develop a general game-theoretic framework for reasoning about strategic agents performing possibly costly computation. In this framework, many traditional game-theoretic results (such as the existence of a Nash equilibrium) no longer…

Computer Science and Game Theory · Computer Science 2008-09-02 Joseph Y. Halpern , Rafael Pass

We introduce a generalization of zero-sum network multiagent matrix games and prove that alternating gradient descent converges to the set of Nash equilibria at rate $O(1/T)$ for this set of games. Alternating gradient descent obtains this…

Computer Science and Game Theory · Computer Science 2021-10-07 James P. Bailey

We study the global convergence of policy optimization for finding the Nash equilibria (NE) in zero-sum linear quadratic (LQ) games. To this end, we first investigate the landscape of LQ games, viewing it as a nonconvex-nonconcave…

Machine Learning · Computer Science 2021-02-12 Kaiqing Zhang , Zhuoran Yang , Tamer Başar

The paper studies the convergence properties of (continuous) best-response dynamics from game theory. Despite their fundamental role in game theory, best-response dynamics are poorly understood in many games of interest due to the…

Optimization and Control · Mathematics 2018-02-08 Brian Swenson , Ryan Murray , Soummya Kar

The uniform distribution is an important counterexample in game theory as many of the canonical game dynamics have been shown not to converge to the equilibrium in certain cases. In particular none of the canonical game dynamics converge to…

Computer Science and Game Theory · Computer Science 2012-07-03 Dashiell E. A. Fryer

The task of computing approximate Nash equilibria in large zero-sum extensive-form games has received a tremendous amount of attention due mainly to the Annual Computer Poker Competition. Immediately after its inception, two competing and…

Artificial Intelligence · Computer Science 2014-11-19 Kevin Waugh , J. Andrew Bagnell

We study the query complexity of approximate notions of Nash equilibrium in games with a large number of players $n$. Our main result states that for $n$-player binary-action games and for constant $\varepsilon$, the query complexity of an…

Computer Science and Game Theory · Computer Science 2014-07-21 Yakov Babichenko

We develop a probabilistic framework to approximate Nash equilibria in symmetric $N$-player games in the large population regime, via the analysis of associated mean field games (MFGs). The approximation is achieved through the analysis of…

Probability · Mathematics 2026-04-27 Ludovic Tangpi , Nizar Touzi
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