Online Nash Equilibrium Seeking with Time-varying Payoff Functions

被引：0
|
作者：
Zheng, Xianxian [1 ]
Zhang, Yichen [1 ]
Tang, Yutao [1 ]
Liu, Chongyuan [1 ]
机构：
[1] Beijing Univ Posts & Telecommun, Sch Artificial Intelligence, Beijing, Peoples R China
来源：
2024 14TH ASIAN CONTROL CONFERENCE, ASCC 2024 | 2024年
基金：
中国国家自然科学基金;
关键词：
distributed algorithm; Nash equilibrium; multi-agent; online game; dynamic regret; GAME;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper, we consider the continuous-time Nash equilibrium seeking problem with time-varying payoff functions. To solve the problem, we first propose an extended version of distributed gradient play algorithms using exact real-time gradients. Then, we discuss its performance from the perspective of online computation, and show that the proposed algorithm can lead to some small dynamic regret providing that the real-time Nash equilibrium does not change too fast. We finally provide a numerical example to illustrate our design.
引用
收藏
页码：2402 / 2406
页数：5
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