江苏省应用数学（中国矿业大学）中心系列学术报告
报告题目：Discrete-time approximation of stochastic optimal control with partial observation
报告人：李运章（复旦大学）
报告时间：2024年5月30日（周四）下午15:00-16:00
报告地点：数学学院A321
主持人：孙永征
报告摘要：We consider a class of stochastic optimal control problems with partial observation, and study their approximation by discrete-time control problems. We establish a convergence result by using the weak convergence technique of Kushner and Dupuis [Numerical Methods for Stochastic Control Problems in Continuous Time, Springer, New York], together with the notion of relaxed 26 (1988), pp. 1025-1061]. In particular, with a well chosen discrete-time control system, we obtain a first implementable numerical algorithm (with convergence) for the partially observed control problem. Moreover, our discrete-time approximation result would open the door to study convergence of more general numerical approximation methods, such as machine learning based methods. Finally, 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. Control. Optim., 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。主持国家自然科学基金委青年科学基金项目，上海市“科技创新行动计划”基础研究领域项目，中国博士后科学基金面上项目，获得复旦大学新工科人才基金资助。