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相关论文: Distributed Nash Equilibrium Seeking under Partial…

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In this paper, the problem of finding a Nash equilibrium of a multi-player game is considered. The players are only aware of their own cost functions as well as the action space of all players. We develop a relatively fast algorithm within…

系统与控制 · 计算机科学 2017-05-09 Farzad Salehisadaghiani , Lacra Pavel

This paper considers a distributed Nash equilibrium seeking problem, where the players only have partial access to other players' actions, such as their neighbors' actions. Thus, the players are supposed to communicate with each other to…

最优化与控制 · 数学 2020-03-31 Yipeng Pang , Guoqiang Hu

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

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

In this paper, Nash equilibrium seeking among a network of players is considered. Different from many existing works on Nash equilibrium seeking in non-cooperative games, the players considered in this paper cannot directly observe the…

最优化与控制 · 数学 2017-03-28 Maojiao Ye , Guoqiang Hu

In this paper, the problem of finding a generalized Nash equilibrium (GNE) of a networked game is studied. Players are only able to choose their decisions from a feasible action set. The feasible set is considered to be a private linear…

计算机科学与博弈论 · 计算机科学 2017-03-27 Farzad Salehisadaghiani , Lacra Pavel

This paper considers a distributed gossip approach for finding a Nash equilibrium in networked games on graphs. In such games a player's cost function may be affected by the actions of any subset of players. An interference graph is…

计算机科学与博弈论 · 计算机科学 2020-04-10 Farzad Salehisadaghiani , Lacra Pavel

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

最优化与控制 · 数学 2025-07-18 Tatiana Tatarenko , Angelia Nedich

We consider a gossip approach for finding a Nash equilibrium in a distributed multi-player network game. We extend previous results on Nash equilibrium seeking to the case when the players' cost functions may be affected by the actions of…

系统与控制 · 计算机科学 2017-05-09 Farzad Salehisadaghiani , Lacra Pavel

In this paper, we address the challenge of Nash equilibrium (NE) seeking in non-cooperative convex games with partial-decision information. We propose a distributed algorithm, where each agent refines its strategy through projected-gradient…

计算机科学与博弈论 · 计算机科学 2023-09-15 Duong Thuy Anh Nguyen , Mattia Bianchi , Florian Dörfler , Duong Tung Nguyen , Angelia Nedić

In practical applications, decision-makers with heterogeneous dynamics may be engaged in the same decision-making process. This motivates us to study distributed Nash equilibrium seeking for games in which players are mixed-order (first-…

最优化与控制 · 数学 2022-09-05 Maojiao Ye , Lei Ding , Jizhao Yin

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 address the generalized Nash equilibrium seeking problem in a partial-decision information scenario, where each agent can only exchange information with some neighbors, although its cost function possibly depends on the strategies of all…

最优化与控制 · 数学 2021-12-14 Mattia Bianchi , Giuseppe Belgioioso , Sergio Grammatico

In this paper we consider the problem of distributed Nash equilibrium (NE) seeking over networks, a setting in which players have limited local information. We start from a continuous-time gradient-play dynamics that converges to an NE…

最优化与控制 · 数学 2024-10-30 Dian Gadjov , Lacra Pavel

Many important real-world settings contain multiple players interacting over an unknown duration with probabilistic state transitions, and are naturally modeled as stochastic games. Prior research on algorithms for stochastic games has…

计算机科学与博弈论 · 计算机科学 2021-02-19 Sam Ganzfried

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 investigates Nash equilibrium (NE) seeking problems for noncooperative games over multi-players networks with finite bandwidth communication. A distributed quantized algorithm is presented, which consists of local gradient play,…

分布式、并行与集群计算 · 计算机科学 2021-11-16 Ziqin Chen , Ji Ma , Shu Liang , Li Li

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

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

In this paper, we aim to develop distributed continuous-time algorithms over directed graphs to seek the Nash equilibrium in a noncooperative game. Motivated by the recent consensus-based designs, we present a distributed algorithm with a…

最优化与控制 · 数学 2022-04-19 Yutao Tang , Peng Yi , Yanqiong Zhang , Dawei Liu
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