时 间：2025年11月4 日（周二）13：30 – 15：00
地 点：普陀校区理科大楼A914室
报告人：嵇少林 山东大学教授
主持人：危佳钦 华东师范大学教授
摘 要：
A novel control method is proposed to solve a high-dimensional stochastic Hamiltonian system with boundary conditions, which is essentially a Forward Backward Stochastic Differential Equation (FBSDE in short). Different from existing methods, we first formulate a stochastic optimal control problem whose extended Hamiltonian system is exactly the system to be solved. Then two different algorithms to calculate the stochastic optimal control via deep neural networks are designed respectively. Comparing with the Deep FBSDE method developed by E et al.（2017）, our proposed algorithms demonstrate more stable performance. （With Shige Peng, Ying Peng and Xichuan Zhang）.
报告人简介：
嵇少林，山东大学教授，1999年获得博士学位，是彭实戈院士创新学术团队成员之一，2011年入选教育部新世纪优秀人才支持计划。研究领域：金融数学、随机控制和非线性期望理论。近年以来，嵇少林教授在Review of Financial Studies, Probability Theory and the Related Fields，Operation Research和SIAM Control and Optimization等杂志上发表了一系列的成果。研究的问题包括模型不确定下的资产定价公式、非线性期望下的Neyman-Pearson基本引理和G-布朗运动驱动下的倒向随机微分方程理论。