This work is concerned with a new class of mean-field games which involve a finite number of agents. Necessary and sufficient conditions are obtained for the existence of the decentralized open-loop Nash equilibrium in terms of non-standard forward-backward stochastic differential equations (FBSDEs). By solving the FBSDEs, we design a set of decentralized strategies by virtue of two differential Riccati equations. Instead of the asymptotic-Nash equilibrium in classical mean-field games, the set of decentralized strategies is shown to be a Nash equilibrium. Comparison with classical results of mean-field games is also discussed.

报告人简介

王炳昌，山东大学副教授，国家优秀青年基金获得者，IEEE Senior Member。2011 年在中国科学院系统科学所获得博士学位，先后在加拿大阿尔伯塔大学和澳大利亚的纽卡斯尔大学做博士后。曾获IEEE Beijing Chapter 青年作者奖、中国控制会议张贴论文奖、亚洲控制会议青年作者奖提名等。目前担任中国自动化学会青年工作委员会委员、区块链专委会委员、控制理论专委会随机学组委员。发表学术论文 60 余篇，包括 IEEE TAC、Automatica 和 SIAM J. Control and Optimization 论文10 余篇(其中长文8 篇）。主要研究方向：随机控制与分布式计算、平均场博弈、机器学习等。