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This paper proposes a distributed algorithm to find the Nash equilibrium in a class of non-cooperative convex games with partial-decision information. Our method employs a distributed projected gradient play approach alongside consensus…

计算机科学与博弈论 · 计算机科学 2024-12-13 Duong Thuy Anh Nguyen , Duong Tung Nguyen , Angelia Nedić

This paper considers the distributed strategy design for Nash equilibrium (NE) seeking in multi-cluster games under a partial-decision information scenario. In the considered game, there are multiple clusters and each cluster consists of a…

最优化与控制 · 数学 2022-06-08 Min Meng , Xiuxian Li

We propose fully-distributed algorithms for Nash equilibrium seeking in aggregative games over networks. We first consider the case where local constraints are present and we design an algorithm combining, for each agent, (i) the projected…

系统与控制 · 电气工程与系统科学 2024-04-04 Guido Carnevale , Filippo Fabiani , Filiberto Fele , Kostas Margellos , Giuseppe Notarstefano

This paper develops a distributed Nash Equilibrium seeking algorithm for heterogeneous multi-robot systems. The algorithm utilises distributed optimisation and output control to achieve the Nash equilibrium by leveraging information shared…

机器人学 · 计算机科学 2025-09-22 Yi Dong , Zhongguo Li , Sarvapali D. Ramchurn , Xiaowei Huang

In noncooperative Nash games, equilibria are often inefficient. This is exemplified by the Prisoner's Dilemma and was first provably shown in the 1980s. Since then, understanding the quality of Nash equilibrium (NE) received considerable…

最优化与控制 · 数学 2024-12-02 Yuyang Qiu , Farzad Yousefian , Brian Zhang

In this paper, we study a distributed continuous-time design for aggregative games with coupled constraints in order to seek the generalized Nash equilibrium by a group of agents via simple local information exchange. To solve the problem,…

最优化与控制 · 数学 2022-06-14 Shu Liang , Peng Yi , Yiguang Hong

This paper aims to design a distributed coordination algorithm for solving a multi-agent decision problem with a hierarchical structure. The primary goal is to search the Nash equilibrium of a noncooperative game such that each player has…

最优化与控制 · 数学 2022-05-17 Xiaoyu Ma , Jinlong Lei , Peng Yi , Jie Chen

Distributed optimization and Nash equilibrium (NE) seeking problems have drawn much attention in the control community recently. This paper studies a class of non-cooperative games, known as N-cluster game, which subsumes both cooperative…

最优化与控制 · 数学 2023-03-01 Yipeng Pang , Guoqiang Hu

Distributed Nash equilibrium (NE) seeking problem for multi-coalition games has attracted increasing attention in recent years, but the research mainly focuses on the case without agreement demand within coalitions. This paper considers a…

最优化与控制 · 数学 2021-12-10 Jialing Zhou , Yuezu Lv , Guanghui Wen , Jinhu Lv , Dezhi Zheng

This work proposes a novel distributed approach for computing a Nash equilibrium in convex games with restricted strongly monotone pseudo-gradients. By leveraging the idea of the centralized operator extrapolation method presented in [4] to…

最优化与控制 · 数学 2023-10-25 Tatiana Tatarenko , Angelia Nedich

In this paper, we investigate a prescribed-time and fully distributed Nash Equilibrium (NE) seeking problem for continuous-time noncooperative games. By exploiting pseudo-gradient play and consensus-based schemes, various distributed NE…

系统与控制 · 电气工程与系统科学 2020-09-25 Zhi Feng , Guoqiang Hu

Distributed Nash equilibrium seeking of aggregative games is investigated and a continuous-time algorithm is proposed. The algorithm is designed by virtue of projected gradient play dynamics and distributed average tracking dynamics, and is…

最优化与控制 · 数学 2021-12-07 Shu Liang , Peng Yi , Yiguang Hong , Kaixiang Peng

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

In this paper, we study the distributed generalized Nash equilibrium seeking problem of non-cooperative games in dynamic environments. Each player in the game aims to minimize its own time-varying cost function subject to a local action…

最优化与控制 · 数学 2020-04-02 Kaihong Lu , Guangqi Li , Long Wang

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 consider the problem of finding a Nash equilibrium in a multi-player game over generally connected networks. This model differs from a conventional setting in that players have partial information on the actions of their…

最优化与控制 · 数学 2019-12-10 Farzad Salehisadaghiani , Wei Shi , Lacra Pavel

This paper studies the distributed generalized Nash equilibrium seeking problem for aggregative games with coupling constraints, where each player optimizes its strategy depending on its local cost function and the estimated strategy…

最优化与控制 · 数学 2025-03-12 Wenqing Zhao , Antai Xie , Yuchi Wu , Xinlei Yi , Xiaoqiang Ren

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

In this paper, we study the problem of the distributed Nash equilibrium seeking of N-player games over jointly strongly connected switching networks. The action of each player is governed by a class of uncertain nonlinear systems. Our…

最优化与控制 · 数学 2024-11-05 Jie Huang

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
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