Discrete-time Approximation of Partially Observed Stochastic Optimal Control Problem
报告题目: Discrete-time Approximation of Partially Observed Stochastic Optimal Control Problem
报告专家: 李运章（复旦大学）
报告时间: 3月29日星期三，下午2:30-4:30
报告地点：国家天元数学西南中心401
报告摘要:In this talk, we study a class of stochastic optimal control problems under partial observation by discrete-time control problems. To establish a convergence result, we adapt the weak convergence technique together with the notion of relaxed control rule. With a well chosen discrete-time control system, we provide an implementable numerical algorithm to approximate the value. We illustrate our convergence result by numerical experiments on a partially observed control problem in a linear quadratic setting.
报告人简介：李运章，复旦大学智能复杂体系实验室青年副研究员。2020年博士毕业于复旦大学数学科学学院。2020年至2022年在复旦大学从事博士后研究工作，期间被聘为香港中文大学名誉博士后。主要研究领域为随机系统的最优控制问题的高阶精度数值算法，相关成果发表于SIAM J. Sci. Comput., SIAM J. Financial Math., ESAIM: M2AN等知名学术期刊。入选上海市晨光计划，国家博士后创新人才支持计划，上海市“超级博士后”激励计划。主持中国博士后科学基金面上资助。
邀请人：王艳艳
