Duality in Deep Reinforcement Learning--Theory

摘要：

　　More and deeper reinforcement learning algorithms have been proposed and demonstrated on a series of decision-making domains.However,little research has been hammered at algorithm extraction.With duality in deep reinforcement learning substantially summarized,we propose a conceptually simple framework for deep reinforcement learning based on duality.Then,we propose the dual method of prioritized sampling: prioritized learning.Finally,we give the formula and analysis for the duality with priority.The algorithm implementation and experiment will be put on Part Ⅱ-Implementation.

关键词： Deep Reinforcement Learning Duality Prioritized Sampling Prioritized Learning

作者: Jie Bai Jianfei Li Zihao Luo Yaobing Wang Li Liu

作者单位: Peking University,Center of Excellence for Intelligent Robotics,Beijing Institute of Spacecraft System Engineering,Beijing,China

会议类型: 国际会议

会议名称: 2019 2nd International Conference on Mechanical, Electronic and Engineering Technology (MEET 2019) 2019年第二届机电与工程技术国际会议

会议地点: 西安

会议语种:英文

页码: 59-66

在线出版日期: 2019-01-19（万方平台首次上网日期，不代表论文的发表时间）