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Revised Progressive-Hedging-Algorithm Based Two-layer Solution Scheme for Bayesian Reinforcement Learning
时间  Datetime
2019-10-28 15:00 — 16:00 
地点  Venue
Large Conference Room(706)
报告人  Speaker
李端
单位  Affiliation
香港城市大学
邀请人  Host
Yi-Shuai Niu
报告摘要  Abstract

Stochastic control with both inherent random system noise and lack of knowledge on system parameters constitutes a fundamental challenge in reinforcement learning, especially under non-episodic setting. We propose a novel two-layer solution scheme to separate reducible system uncertainty from irreducible one at two layers (adopting time-composition based DP at the lower layer and the scenario-decomposition based progressive hedging algorithm at the upper layer) and to approximate the optimal policy directly. Applications in dynamic portfolio selection will be discussed.