Exponentially convergent distributed Nash equilibrium seeking for constrained aggregative games

Autonomous Intelligent Systems

Shu Liang¹  Peng Yi¹  Yiguang Hong¹  Kaixiang Peng² 

[1] Department of Control Science & Engineering, Tongji University;School of Automation and Electrical Engineering, University of Science and Technology Beijing;

关键词: Distributed algorithms;    Aggregative games;    Projected gradient play;    Weight-balanced graph;    Exponential convergence;   

DOI  :  10.1007/s43684-022-00024-4

来源: DOAJ

【 摘 要 】

Abstract 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 aggregation tracking dynamics, and is applicable to games with constrained strategy sets and weight-balanced communication graphs. The key feature of our method is that the proposed projected dynamics achieves exponential convergence, whereas such convergence results are only obtained for non-projected dynamics in existing works on distributed optimization and equilibrium seeking. Numerical examples illustrate the effectiveness of our methods.

【 授权许可】

Unknown