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Decentralized online learning for seeking generalized Nash equilibrium (GNE) of noncooperative games in dynamic environments is studied in this paper. Each player aims at selfishly minimizing its own time-varying cost function subject to…

最优化与控制 · 数学 2021-05-14 Min Meng , Xiuxian Li , Yiguang Hong , Jie Chen , Long Wang

Coordination in multiplayer games enables players to avoid the lose-lose outcome that often arises at Nash equilibria. However, designing a coordination mechanism typically requires the consideration of the joint actions of all players,…

计算机科学与博弈论 · 计算机科学 2026-03-23 Jaehan Im , Yue Yu , David Fridovich-Keil , Ufuk Topcu

We study a very general class of games --- multi-dimensional aggregative games --- which in particular generalize both anonymous games and weighted congestion games. For any such game that is also large, we solve the equilibrium selection…

数据结构与算法 · 计算机科学 2015-02-26 Rachel Cummings , Michael Kearns , Aaron Roth , Zhiwei Steven Wu

Graphical games are a useful framework for modeling the interactions of (selfish) agents who are connected via an underlying topology and whose behaviors influence each other. They have wide applications ranging from computer science to…

计算机科学与博弈论 · 计算机科学 2021-04-27 Juho Hirvonen , Laura Schmid , Krishnendu Chatterjee , Stefan Schmid

In this paper, we propose an asynchronous distributed algorithm for the computation of generalized Nash equilibria in noncooperative games, where the players interact via an undirected communication graph. Specifically, we extend the paper…

计算机科学与博弈论 · 计算机科学 2024-12-20 Carlo Cenedese , Giuseppe Belgioioso , Sergio Grammatico , Ming Cao

We consider multi-agent decision making, where each agent optimizes its cost function subject to constraints. Agents' actions belong to a compact convex Euclidean space and the agents' cost functions are coupled. We propose a distributed…

最优化与控制 · 数学 2016-12-01 Tatiana Tatarenko , Maryam Kamgarpour

Due to the lack of coordination, it is unlikely that the selfish players of a strategic game reach a socially good state. A possible way to cope with selfishness is to compute a desired outcome (if it is tractable) and impose it. However…

计算机科学与博弈论 · 计算机科学 2010-12-20 Bruno Escoffier , Laurent Gourvès , Jérôme Monnot

In this paper, we present a novel consensus-based zeroth-order algorithm tailored for non-convex multiplayer games. The proposed method leverages a metaheuristic approach using concepts from swarm intelligence to reliably identify global…

动力系统 · 数学 2024-07-30 Enis Chenchene , Hui Huang , Jinniao Qiu

In this paper, a distributed non-model based seeking algorithm which combines the extremum seeking control (ESC) jointly with learning algorithms is proposed to seek a generalized Nash equilibrium (GNE) for a class of noncooperative games…

最优化与控制 · 数学 2023-02-27 Feng Xiao , Xin Cai , Bo Wei

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…

最优化与控制 · 数学 2025-05-13 Yulong Lu , Pierre Monmarché

This paper aims to accommodate games in which the players' dynamics are subject to un-modeled and disturbance terms. The un-modeled and disturbance terms are regarded as extended states for which observers are designed to estimate them.…

最优化与控制 · 数学 2020-04-22 Maojiao Ye

Current research in distributed Nash equilibrium (NE) seeking in the partial information setting assumes that information is exchanged between agents that are "truthful". However, in general noncooperative games agents may consider sending…

最优化与控制 · 数学 2021-11-30 Dian Gadjov , Lacra Pavel

This paper explores distributed aggregative games in multi-agent systems. Current methods for finding distributed Nash equilibrium require players to send original messages to their neighbors, leading to communication burden and privacy…

系统与控制 · 电气工程与系统科学 2024-05-07 Wei Huo , Xiaomeng Chen , Kemi Ding , Subhrakanti Dey , Ling Shi

This paper presents a new primal-dual method for computing an equilibrium of generalized (continuous) Nash game (referred to as generalized Nash equilibrium problem (GNEP)) where each player's feasible strategy set depends on the other…

计算机科学与博弈论 · 计算机科学 2022-03-04 Jong Gwang Kim

We study techniques to incentivize self-interested agents to form socially desirable solutions in scenarios where they benefit from mutual coordination. Towards this end, we consider coordination games where agents have different intrinsic…

计算机科学与博弈论 · 计算机科学 2014-04-21 Elliot Anshelevich , Shreyas Sekar

We study the computation of equilibria of anonymous games, via algorithms that may proceed via a sequence of adaptive queries to the game's payoff function, assumed to be unknown initially. The general topic we consider is \emph{query…

计算机科学与博弈论 · 计算机科学 2016-05-06 Paul W. Goldberg , Stefano Turchetta

This paper investigates the privacy-preserving distributed Nash equilibrium seeking problem for aggregative games. A novel differential privacy mechanism is designed by incorporating stochastic event-triggering with stochastic quantization,…

最优化与控制 · 数学 2026-05-27 Qingtan Meng , Qian Ma

Establishing the existence of Nash equilibria for partially observed stochastic dynamic games is known to be quite challenging, with the difficulties stemming from the noisy nature of the measurements available to individual players…

系统与控制 · 计算机科学 2018-06-06 Naci Saldi , Tamer Basar , Maxim Raginsky

This paper investigates a fully distributed adaptive Nash equilibrium (NE) seeking algorithm for constrained noncooperative games with prescribed-time stability. On the one hand, prescribed-time stability for the proposed NE seeking…

最优化与控制 · 数学 2024-11-07 Sichen Qian

Nash equilibrium is one of the most influential solution concepts in game theory. With the development of computer science and artificial intelligence, there is an increasing demand on Nash equilibrium computation, especially for Internet…

计算机科学与博弈论 · 计算机科学 2023-12-19 Hanyu Li , Wenhan Huang , Zhijian Duan , David Henry Mguni , Kun Shao , Jun Wang , Xiaotie Deng