Exponentially convergent distributed Nash equilibrium seeking for constrained aggregative games  

作　　者：Shu Liang Peng Yi Yiguang Hong Kaixiang Peng 

机构地区：[1]Department of Control Science&Engineering,Tongji University,Shanghai,200092,China [2]Shanghai Research Institute for Intelligent Autonomous Systems,Shanghai,201210,China [3]School of Automation and Electrical Engineering,University of Science and Technology Beijing,Beijing,100083,China

出　　处：《Autonomous Intelligent Systems》2022年第1期71-78,共8页自主智能系统（英文）

基　　金：This work was partially supported by the National Natural Science Foundation of China under Grant 61903027,72171171,62003239;Shanghai Municipal Science and Technology Major Project under Grant 2021SHZDZX0100;Shanghai Sailing Program under Grant 20YF1453000.

摘　　要：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.

关 键 词：Distributed algorithms Aggregative games Projected gradient play Weight-balanced graph Exponential convergence 

分 类 号：O17[理学—数学]