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We consider a game in which the action set of each player is uncountable, and show that, from weak assumptions on the common prior, any mixed strategy has an approximately equivalent pure strategy. The assumption of this result can be…

Theoretical Economics · Economics 2023-02-15 Yuhki Hosoya , Chaowen Yu

We study policy optimization algorithms for computing correlated equilibria in multi-player general-sum Markov Games. Previous results achieve $O(T^{-1/2})$ convergence rate to a correlated equilibrium and an accelerated $O(T^{-3/4})$…

Machine Learning · Computer Science 2024-05-03 Yang Cai , Haipeng Luo , Chen-Yu Wei , Weiqiang Zheng

The approximation of mixed Nash equilibria (MNE) for zero-sum games with mean-field interacting players has recently raised much interest in machine learning. In this paper we propose a mean-field gradient descent dynamics for finding the…

Optimization and Control · Mathematics 2025-05-13 Yulong Lu , Pierre Monmarché

Computational aspects of solution notions such as Nash equilibrium have been extensively studied, including settings where the ultimate goal is to find an equilibrium that possesses some additional properties. Furthermore, in order to…

Computational Complexity · Computer Science 2023-05-09 Bruce M. Kapron , Koosha Samieefar

In this paper we propose a numerical method to obtain an approximation of Nash equilibria for multi-player non-cooperative games with a special structure. We consider the infinite horizon problem in a case which leads to a system of…

Numerical Analysis · Mathematics 2016-02-19 Simone Cacace , Emiliano Cristiani , Maurizio Falcone

In this paper, we present exploitability descent, a new algorithm to compute approximate equilibria in two-player zero-sum extensive-form games with imperfect information, by direct policy optimization against worst-case opponents. We prove…

Artificial Intelligence · Computer Science 2020-06-15 Edward Lockhart , Marc Lanctot , Julien Pérolat , Jean-Baptiste Lespiau , Dustin Morrill , Finbarr Timbers , Karl Tuyls

We design a computational approach to find equilibria in a class of Nash games possessing a hierarchical structure. By using tools from mixed-integer optimization and the characterization of variational equilibria in terms of the…

Optimization and Control · Mathematics 2024-11-12 Barbara Franci , Filippo Fabiani , Martin Schmidt , Mathias Staudigl

In large-scale games, approximating the opponent's strategy space with a small portfolio of representative strategies is a common and powerful technique. However, the construction of these portfolios often relies on domain-specific…

Computer Science and Game Theory · Computer Science 2025-11-25 Karolina Drabent , Ondřej Kubíček , Viliam Lisý

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

Synthesis of finite-state controllers from high-level specifications in multi-agent systems can be reduced to solving multi-player concurrent games over finite graphs. The complexity of solving such games with qualitative objectives for…

Computer Science and Game Theory · Computer Science 2018-09-28 Shaull Almagor , Rajeev Alur , Suguman Bansal

In this tutorial, we provide an introduction to machine learning methods for finding Nash equilibria in games with large number of agents. These types of problems are important for the operations research community because of their…

Optimization and Control · Mathematics 2024-06-18 Gokce Dayanikli , Mathieu Lauriere

Reinforcement learning for multi-agent games has attracted lots of attention recently. However, given the challenge of solving Nash equilibria for large population games, existing works with guaranteed polynomial complexities either focus…

Optimization and Control · Mathematics 2025-09-04 Anran Hu , Junzi Zhang

We study two-player general sum repeated finite games where the rewards of each player are generated from an unknown distribution. Our aim is to find the egalitarian bargaining solution (EBS) for the repeated game, which can lead to much…

Machine Learning · Computer Science 2019-06-05 Aristide Tossou , Christos Dimitrakakis , Jaroslaw Rzepecki , Katja Hofmann

Two-team zero-sum games are one of the most important paradigms in game theory. In this paper, we focus on finding an unexploitable equilibrium in large team games. An unexploitable equilibrium is a worst-case policy, where members in the…

Computer Science and Game Theory · Computer Science 2024-03-04 Naming Liu , Mingzhi Wang , Youzhi Zhang , Yaodong Yang , Bo An , Ying Wen

We study a distributed approach for seeking a Nash equilibrium in $n$-cluster games with strictly monotone mappings. Each player within each cluster has access to the current value of her own smooth local cost function estimated by a…

Computer Science and Game Theory · Computer Science 2021-07-28 Tatiana Tatarenko , Jan Zimmermann , Jürgen Adamy

We consider $\epsilon$-equilibria notions for constant value of $\epsilon$ in $n$-player $m$-actions games where $m$ is a constant. We focus on the following question: What is the largest grid size over the mixed strategies such that…

Computer Science and Game Theory · Computer Science 2017-01-30 Itai Arieli , Yakov Babichenko

We consider quadratic, nonmonotone generalized Nash equilibrium problems with symmetric interactions among the agents. Albeit this class of games is known to admit a potential function, its formal expression can be unavailable in several…

Optimization and Control · Mathematics 2022-03-31 Filippo Fabiani , Andrea Simonetto , Paul J. Goulart

In competitive multi-player interactions, simultaneous optimality is a key requirement for establishing strategic equilibria. This property is explicit when the game-theoretic equilibrium is the simultaneously optimal solution of coupled…

Computer Science and Game Theory · Computer Science 2024-04-04 Sarah H. Q. Li , Yue Yu , Florian Dörfler , John Lygeros

Learning problems commonly exhibit an interesting feedback mechanism wherein the population data reacts to competing decision makers' actions. This paper formulates a new game theoretic framework for this phenomenon, called "multi-player…

Computer Science and Game Theory · Computer Science 2022-04-08 Adhyyan Narang , Evan Faulkner , Dmitriy Drusvyatskiy , Maryam Fazel , Lillian J. Ratliff

We present an algorithm for computing evolutionarily stable strategies (ESSs) in symmetric perfect-recall extensive-form games of imperfect information. Our main algorithm is for two-player games, and we describe how it can be extended to…

Computer Science and Game Theory · Computer Science 2025-12-15 Sam Ganzfried
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