A Linearly Convergent Distributed Nash Equilibrium Seeking Algorithm for Aggregative Games

• 成果类型: Article
• 署名作者: Huang, Shijie; Lei, Jinlong; Hong, Yiguang
• 署名单位: Chinese Academy of Sciences; Academy of Mathematics & System Sciences, CAS; Tongji University
• 刊物名称: IEEE TRANSACTIONS ON AUTOMATIC CONTROL
• ISSN/ISSBN: 0018-9286
• DOI: 10.1109/TAC.2022.3154356
• 发表日期: 2023
• 页码: 1753-1759
• 关键词: games; CONVERGENCE; Distributed algorithms; Aggregates; Nash equilibrium; Heuristic algorithms; Eigenvalues and eigenfunctions; Aggregative games; distributed Nash equilibrium (NE) seeking; linear convergence

摘要

This article considers distributed Nash equilibrium (NE) seeking of strongly monotone aggregative games over a multiagent network. Each player can only observe its own strategy while can exchange information with its neighbors via a communication graph. To solve the problem, we propose a distributed algorithm with multiple rounds of communication, where the players need constant rounds of communication with their neighbors at each iteration. We then prove that our algorithm converges to the (unique) NE with a linear convergence rate. We further study a single-round communication version of our algorithm, which can also achieve linear convergence rate with an additional condition related to the structure of the graph and the properties of the aggregative game. Finally, we provide numerical simulations to verify our results.