报告题目：

Linear-Quadratic Delayed Mean-Field Social Optimization

报 告 人：王树军

工作单位：山东大学

报告时间：4月8日（周六）9：30-11：30

报告地点：实训中心1705

报告摘要：

A linear quadratic (LQ) stochastic optimization problem with delay involving weakly-coupled large population is investigated in this paper. Different to classic mean field (MF) game, here agents cooperate with each other to minimize the so-called social objective. With the aid of delayed person-by-person optimality principle, one arrives at an auxiliary LQ delayed control problem by decentralized information. A decentralized strategy is obtained by feat of an MF type anticipated forward-backward stochastic differential delay equation (AFBSDDE) consistency condition. The discounting method with delay feature is employed to solve the consistency condition system. Finally, by some estimates of AFBSDDEs we derive the asymptotic social optimality.

报告人简介：

王树军，山东大学管理学院副研究员，泰山学者青年专家。2009年获得山东大学理学学士学位，2016年分别获得香港理工大学和山东大学理学博士学位。研究方向包括随机控制、随机平均场博弈、正倒向随机微分方程等，研究成果发表在IEEE TAC、AMO等控制论主流期刊。主持国家自然科学青年基金，入选山东大学青年学者未来计划等。