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Stochastic games generalize Markov decision processes (MDPs) to a multiagent setting by allowing the state transitions to depend jointly on all player actions, and having rewards determined by multiplayer matrix games at each state. We…

计算机科学与博弈论 · 计算机科学 2013-01-18 Michael Kearns , Yishay Mansour , Satinder Singh

This paper studies an $N$-coalition non-cooperative game problem, where the players in the same coalition cooperatively minimize the sum of their local cost functions under a directed communication graph, while collectively acting as a…

最优化与控制 · 数学 2021-09-13 Yipeng Pang , Guoqiang Hu

We consider the problem of computing Nash equilibria in potential games where each player's strategy set is subject to private uncoupled constraints. This scenario is frequently encountered in real-world applications like road network…

计算机科学与博弈论 · 计算机科学 2024-02-13 Nikolas Patris , Stelios Stavroulakis , Fivos Kalogiannis , Rose Zhang , Ioannis Panageas

Behavioral diversity, expert imitation, fairness, safety goals and others give rise to preferences in sequential decision making domains that do not decompose additively across time. We introduce the class of convex Markov games that allow…

计算机科学与博弈论 · 计算机科学 2025-06-17 Ian Gemp , Andreas Haupt , Luke Marris , Siqi Liu , Georgios Piliouras

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…

计算机科学与博弈论 · 计算机科学 2017-03-07 Julien Pérolat , Florian Strub , Bilal Piot , Olivier Pietquin

We suggest a novel stochastic-approximation algorithm to compute a symmetric Nash-equilibrium strategy in a general queueing game with a finite action space. The algorithm involves a single simulation of the queueing process with dynamic…

概率论 · 数学 2023-08-30 Liron Ravner , Ran I. Snitkovsky

We present a simple primal-dual algorithm for computing approximate Nash-equilibria in two-person zero-sum sequential games with incomplete information and perfect recall (like Texas Hold'em Poker). Our algorithm is numerically stable,…

计算机科学与博弈论 · 计算机科学 2015-12-24 Elvis Dohmatob

We solve the stochastic generalized Nash equilibrium (SGNE) problem in merely monotone games with expected value cost functions. Specifically, we present the first distributed SGNE seeking algorithm for monotone games that requires one…

最优化与控制 · 数学 2021-07-15 Barbara Franci , Sergio Grammatico

This paper considers data-based solutions of linear-quadratic nonzero-sum differential games. Two cases are considered. First, the deterministic game is solved and Nash equilibrium strategies are obtained by using persistently excited data…

系统与控制 · 电气工程与系统科学 2026-05-15 Victor G. Lopez , Matthias A. Müller

Nash equilibrium is a solution concept in non-strictly competitive, non-cooperative game theory that finds applications in various scientific and engineering disciplines. A non-strictly competitive, non-cooperative game model is presented…

量子物理 · 物理学 2015-02-05 Faisal Shah Khan

In this paper we present a novel generic mapping between Graphical Games and Markov Random Fields so that pure Nash equilibria in the former can be found by statistical inference on the latter. Thus, the problem of deciding whether a…

计算机科学与博弈论 · 计算机科学 2007-05-23 Constantinos Daskalakis

In an inverse game problem, one needs to infer the cost function of the players in a game such that a desired joint strategy is a Nash equilibrium. We study the inverse game problem for a class of multiplayer matrix games, where the cost…

计算机科学与博弈论 · 计算机科学 2022-10-17 Yue Yu , Jonathan Salfity , David Fridovich-Keil , Ufuk Topcu

This paper considers a class of noncooperative games in which the feasible decision sets of all players are coupled together by a coupled inequality constraint. Adopting the variational inequality formulation of the game, we first introduce…

计算机科学与博弈论 · 计算机科学 2024-02-13 Huaqing Li , Liang Ran , Lifeng Zheng , Zhe Li , Jinhui Hu , Jun Li , Tingwen Huang

In this paper, we study the problem of learning the set of pure strategy Nash equilibria and the exact structure of a continuous-action graphical game with quadratic payoffs by observing a small set of perturbed equilibria. A…

计算机科学与博弈论 · 计算机科学 2019-11-12 Adarsh Barik , Jean Honorio

In this work, we study stochastic non-cooperative games, where only noisy black-box function evaluations are available to estimate the cost function for each player. Since each player's cost function depends on both its own decision…

计算机科学与博弈论 · 计算机科学 2025-11-18 Haidong Li , Anzhi Sheng , Yijie Peng , Long Wang

We identify structural assumptions which provide solvability of the Nash system arising from a linear-quadratic closed-loop game, with stable properties with respect to the number of players. In a setting of interactions governed by a…

最优化与控制 · 数学 2024-01-15 Marco Cirant , Davide Francesco Redaelli

The set of Nash equilibria of a finite game is the set of nonnegative solutions to a system of polynomial equations. In this survey article we describe how to construct certain special games and explain how to find all the complex roots of…

交换代数 · 数学 2007-05-23 Ruchira S. Datta

We develop provably efficient reinforcement learning algorithms for two-player zero-sum finite-horizon Markov games with simultaneous moves. To incorporate function approximation, we consider a family of Markov games where the reward…

机器学习 · 计算机科学 2020-06-25 Qiaomin Xie , Yudong Chen , Zhaoran Wang , Zhuoran Yang

In this paper, a multi-cluster game with high-order players is investigated. Different from the well-known multi-cluster games, the dynamics of players are taken into account in our problem. Due to the high-order dynamics of players,…

系统与控制 · 电气工程与系统科学 2021-06-28 Zhenhua Deng , Yangyang Liu

Nash equilibrium has long been a desired solution concept in multi-player games, especially for those on continuous strategy spaces, which have attracted a rapidly growing amount of interests due to advances in research applications such as…

计算机科学与博弈论 · 计算机科学 2019-10-29 Zehao Dou , Xiang Yan , Dongge Wang , Xiaotie Deng