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Related papers: Zero-Sum Games and Linear Programming Duality

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Synthesizing near-optimal mixed strategies for zero-sum differential games (ZSDGs) has been a longstanding challenge. Existing research mainly focuses on characterizing the theoretical value function, while the practical design of…

Optimization and Control · Mathematics 2026-05-13 Tao Xu , Wang Xi , Jianping He

In this paper we study two-player bilinear zero-sum games with constrained strategy spaces. An instance of natural occurrences of such constraints is when mixed strategies are used, which correspond to a probability simplex constraint. We…

Computer Science and Game Theory · Computer Science 2022-06-10 Andre Wibisono , Molei Tao , Georgios Piliouras

Learning from repeated play in a fixed two-player zero-sum game is a classic problem in game theory and online learning. We consider a variant of this problem where the game payoff matrix changes over time, possibly in an adversarial…

Machine Learning · Computer Science 2022-02-01 Mengxiao Zhang , Peng Zhao , Haipeng Luo , Zhi-Hua Zhou

Shapley's discounted stochastic games, Everett's recursive games and Gillette's undiscounted stochastic games are classical models of game theory describing two-player zero-sum games of potentially infinite duration. We describe algorithms…

Computer Science and Game Theory · Computer Science 2012-02-20 Kristoffer Arnsfelt Hansen , Michal Koucky , Niels Lauritzen , Peter Bro Miltersen , Elias Tsigaridas

The min-max optimization problem, also known as the saddle point problem, is a classical optimization problem which is also studied in the context of zero-sum games. Given a class of objective functions, the goal is to find a value for the…

Optimization and Control · Mathematics 2021-08-11 Meisam Razaviyayn , Tianjian Huang , Songtao Lu , Maher Nouiehed , Maziar Sanjabi , Mingyi Hong

Optimization under uncertainty is a fundamental problem in learning and decision-making, particularly in multi-agent systems. Previously, Feldman, Kalai, and Tennenholtz [2010] demonstrated the ability to efficiently compete in repeated…

Computer Science and Game Theory · Computer Science 2026-01-29 Daniel Ablin , Alon Cohen

We consider two person zero-sum games where the players control, at discrete times {tn} induced by a partition $\Pi$ of R + , a continuous time Markov state process. We prove that the limit of the values v$\Pi$ exist as the mesh of $\Pi$…

Optimization and Control · Mathematics 2016-03-31 Sylvain Sorin

The behavior of games repeated in parallel, when played with quantumly entangled players, has received much attention in recent years. Quantum analogues of Raz's classical parallel repetition theorem have been proved for many special…

Quantum Physics · Physics 2016-04-18 Henry Yuen

A new solution concept for two-player zero-sum matrix games with multi-dimensional payoff is introduced. It is based on extensions of vector orders in K-dimensional spaces to order relations in their power sets, so-called set relations, and…

Optimization and Control · Mathematics 2017-01-31 Andreas H. Hamel , Andreas Loehne

We consider the relation between Sion's minimax theorem for a continuous function and a Nash equilibrium in a five-players game with two groups which is zero-sum and symmetric in each group. We will show the following results. 1. The…

General Economics · Economics 2018-09-10 Atsuhiro Satoh , Yasuhito Tanaka

Symmetry is inherent in the definition of most of the two-player zero-sum games, including parity, mean-payoff, and discounted-payoff games. It is therefore quite surprising that no symmetric analysis techniques for these games exist. We…

Computer Science and Game Theory · Computer Science 2015-01-27 Sven Schewe , Ashutosh Trivedi , Thomas Varghese

Many recent AI architectures are inspired by zero-sum games, however, the behavior of their dynamics is still not well understood. Inspired by this, we study standard gradient descent ascent (GDA) dynamics in a specific class of non-convex…

Optimization and Control · Mathematics 2021-01-14 Lampros Flokas , Emmanouil-Vasileios Vlatakis-Gkaragkounis , Georgios Piliouras

Decentralized team problems where players have asymmetric information about the state of the underlying stochastic system have been actively studied, but \emph{games} between such teams are less understood. We consider a general model of…

Multiagent Systems · Computer Science 2021-09-29 Dhruva Kartik , Ashutosh Nayyar , Urbashi Mitra

We develop the fictitious play algorithm in the context of the linear programming approach for mean field games of optimal stopping and mean field games with regular control and absorption. This algorithm allows to approximate the mean…

Optimization and Control · Mathematics 2023-01-25 Roxana Dumitrescu , Marcos Leutscher , Peter Tankov

In this invited contribution, we propose a comprehensive introduction to game theory applied in computer aided synthesis. In this context, we give some classical results on two-player zero-sum games and then on multi-player non zero-sum…

Computer Science and Game Theory · Computer Science 2017-06-05 Véronique Bruyère

Min-max optimization problems (i.e., min-max games) have been attracting a great deal of attention because of their applicability to a wide range of machine learning problems. Although significant progress has been made recently, the…

Computer Science and Game Theory · Computer Science 2023-07-07 Denizalp Goktas , Amy Greenwald

We introduce a new approach for computing optimal equilibria via learning in games. It applies to extensive-form settings with any number of players, including mechanism design, information design, and solution concepts such as correlated,…

Bayesian regression games are a special class of two-player general-sum Bayesian games in which the learner is partially informed about the adversary's objective through a Bayesian prior. This formulation captures the uncertainty in regard…

Machine Learning · Computer Science 2021-10-04 Wenshuo Guo , Michael I. Jordan , Tianyi Lin

Fuzzy Set Theory has been applied in many fields such as Operations Research, Control Theory, and Management Sciences etc. In particular, an application of this theory in Managerial Decision Making Problems has a remarkable significance. In…

Artificial Intelligence · Computer Science 2013-07-09 Arindam Chaudhuri

We prove sufficient and necessary conditions ensuring zero duality gap for Lagrangian duality in some classes of nonconvex optimization problems. To this aim, we use the $\Phi$-convexity theory and minimax theorems for $\Phi$-convex…

Optimization and Control · Mathematics 2024-01-11 Ewa Bednarczuk , Monika Syga