An asymmetric information mean-field type LQ stochastic Stackelberg differential game
报告人：Guangchen Wang
报告人单位：山东大学
时间：22年6月22日（周三）晚上 7：30~8：30
线上腾讯会议号：207-756-307 密码：610064
摘要：This talk is concerned with an asymmetric information LQ stochastic Stackelberg differential game with one leader and two followers, where the game system is governed by mean-field type stochastic differential equation. With the help of some systems of Riccati equations, the followers solve an MF-type stochastic LQ game problem with partial information first, and then, the leader turns to address an optimal control problem driven by linear mean-field type forward-backward stochastic differential filtering equation. By maximum principle, direct construction method and optimal filtering, the open-loop Stackelberg solution is expressed as a feedback form of state, state estimation, and state mean.
报告人简介：王光臣，山东大学控制科学与工程学院教授，首批青年长江学者。一直从事基于不完备信息的随机系统优化控制理论研究，取得了以倒向分离原理为特色的理论与应用成果，在Springer出版社出版英文专著1部，在控制理论国际知名期刊SIAM J. Control Optim.、Automatica和IEEE-TAC发表学术论文10余篇，目前主持国家杰青项目1项，曾获省部级科技奖3项，陈翰馥奖1项。
邀请人：宋恩彬 教授
