Promoting Quality and Diversity in Population-based Reinforcement Learning via Hierarchical Trajectory Space Exploration
Jiayu Miao,Tianze Zhou,Kun Shao,Ming Zhou,Weinan Zhang,Jianye Hao,Yong Yu,Jun Wang,Jiayu Miao,Tianze Zhou,Kun Shao,Ming Zhou,Weinan Zhang,Jianye Hao,Yong Yu,Jun Wang
Quality Diversity (QD) algorithms in population-based reinforcement learning aim to optimize agents' returns and diversity among the population simultaneously. It is conducive to solving exploration problems in reinforcement learning and potentially getting multiple good and diverse strategies. However, previous methods typically define behavioral embedding in action space or outcome space, which ...
