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In this work, we investigate the distributed generalized Nash equilibrium (GNE) seeking problems for $N$-coalition games with inequality constraints. First, we study the scenario where each agent in a coalition has full information of all…

最优化与控制 · 数学 2021-09-28 Chao Sun , Guoqiang Hu

We propose a new approach to mean field games with major and minor players. Our formulation involves a two player game where the optimization of the representative minor player is standard while the major player faces an optimization over…

概率论 · 数学 2014-09-26 Rene Carmona , Xiuneng Zhu

We design the first fully-distributed algorithm for generalized Nash equilibrium seeking in aggregative games on a time-varying communication network, under partial-decision information, i.e., the agents have no direct access to the…

最优化与控制 · 数学 2022-06-16 Giuseppe Belgioioso , Angelia Nedić , Sergio Grammatico

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…

计算机科学与博弈论 · 计算机科学 2021-07-28 Tatiana Tatarenko , Jan Zimmermann , Jürgen Adamy

We consider mean field games with discrete state spaces (called discrete mean field games in the following) and we analyze these games in continuous and discrete time, over finite as well as infinite time horizons. We prove the existence of…

最优化与控制 · 数学 2019-09-04 Josu Doncel , Nicolas Gast , Bruno Gaujal

We consider two classes of constrained finite state-action stochastic games. First, we consider a two player nonzero sum single controller constrained stochastic game with both average and discounted cost criterion. We consider the same…

最优化与控制 · 数学 2012-06-11 Vikas Vikram Singh , N. Hemachandra

Recent advances in multiagent learning have seen the introduction ofa family of algorithms that revolve around the population-based trainingmethod PSRO, showing convergence to Nash, correlated and coarse corre-lated equilibria. Notably,…

计算机科学与博弈论 · 计算机科学 2022-08-30 Paul Muller , Mark Rowland , Romuald Elie , Georgios Piliouras , Julien Perolat , Mathieu Lauriere , Raphael Marinier , Olivier Pietquin , Karl Tuyls

We address in this paper Reinforcement Learning (RL) among agents that are grouped into teams such that there is cooperation within each team but general-sum (non-zero sum) competition across different teams. To develop an RL method that…

机器学习 · 计算机科学 2025-02-11 Muhammad Aneeq uz Zaman , Alec Koppel , Mathieu Laurière , Tamer Başar

We study the convergence of Optimistic Gradient Descent Ascent in unconstrained bilinear games. In a first part, we consider the zero-sum case and extend previous results by Daskalakis et al. in 2018, Liang and Stokes in 2019, and others:…

最优化与控制 · 数学 2022-11-24 Étienne de Montbrun , Jérôme Renault

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…

计算机科学与博弈论 · 计算机科学 2024-05-07 Xinrun Wang , Chang Yang , Shuxin Li , Pengdeng Li , Xiao Huang , Hau Chan , Bo An

We study the problem of computing an approximate Nash equilibrium of a game whose strategy space is continuous without access to gradients of the utility function. Such games arise, for example, when players' strategies are represented by…

计算机科学与博弈论 · 计算机科学 2025-10-28 Carlos Martin , Tuomas Sandholm

Decision-making in multi-player games can be extremely challenging, particularly under uncertainty. In this work, we propose a new sample-based approximation to a class of stochastic, general-sum, pure Nash games, where each player has an…

In this work, we study the distributed Nash equilibrium seeking problem for monotone generalized noncooperative games with set constraints and shared affine inequality constraints. A distributed regularized penalty method is proposed. The…

最优化与控制 · 数学 2021-09-28 Chao Sun , Guoqiang Hu

In this paper we develop a novel approach to the convergence of Best-Response Dynamics for the family of interference games. Interference games represent the fundamental resource allocation conflict between users of the radio spectrum. In…

计算机科学与博弈论 · 计算机科学 2018-11-20 Ilai Bistritz , Amir Leshem

Finding equilibria via gradient play in competitive multi-agent games has been attracting a growing amount of attention in recent years, with emphasis on designing efficient strategies where the agents operate in a decentralized and…

计算机科学与博弈论 · 计算机科学 2022-11-17 Ruicheng Ao , Shicong Cen , Yuejie Chi

We consider distributed computation of generalized Nash equilibrium (GNE) over networks, in games with shared coupling constraints. Existing methods require that each player has full access to opponents' decisions. In this paper, we assume…

最优化与控制 · 数学 2024-10-30 Lacra Pavel

This paper addresses the problem of distributed online generalized Nash equilibrium (GNE) learning for multi-cluster games with delayed feedback information. Specifically, each agent in the game is assumed to be informed a sequence of local…

最优化与控制 · 数学 2024-07-08 Bingqian Liu , Guanghui Wen , Xiao Fang , Tingwen Huang , Guanrong Chen

Continuous games are multiplayer games in which strategy sets are compact and utility functions are continuous. These games typically have a highly complicated structure of Nash equilibria, and numerical methods for the equilibrium…

计算机科学与博弈论 · 计算机科学 2022-07-12 T. Kroupa , T. Votroubek

We introduce a novel class of Nash equilibrium seeking dynamics for non-cooperative games with a finite number of players, where the convergence to the Nash equilibrium is bounded by a KL function with a settling time that can be upper…

最优化与控制 · 数学 2020-12-25 Jorge I. Poveda , Miroslav Krstic , Tamer Basar

We study the convergence of Nash equilibria in a game of optimal stopping. If the associated mean field game has a unique equilibrium, any sequence of $n$-player equilibria converges to it as $n\to\infty$. However, both the finite and…

最优化与控制 · 数学 2019-05-30 Marcel Nutz , Jaime San Martin , Xiaowei Tan