报告题目：Stochastic Game of Finite Fuel Problem
报告人：徐任远，University of California, Berkeley
时间：12月26号（周二），下午2:00-3:00
地点：五教 5205
摘要：In general, finding a Nash equilibrium (NE) or proving Pareto optimality (PO) for continuous-time stochastic game with multiple players is hard, even when there are only two players in the game. Mean Field Game (MFG) provides a powerful tool and analytically feasible framework to approximate the NE and the PO of the N-player stochastic games. In this talk, we will first present the stochastic game for the classical finite fuel follower problem in the seminal paper by Benes, Shepp, and Witsenhausen (1980). We will then solve and compare with explicit solutions for the NE and the PO of the N-player game, and the corresponding MFG when the number of players goes to infinity. This is a joint work with Professor Xin Guo from UC Berkeley.
Bio: Renyuan Xu is a fourth-year Ph.D. candidate in Industrial Engineering and Operations Research (IEOR) Department at UC Berkeley where she works under the supervision of Professor Xin Guo. Her research focuses on the interface between machine learning, and stochastic optimization and control, with applications on big data especially high frequency trading. She received a bachelor’s degree in Mathematics from University of Science and Technology of China (USTC) in 2014.