Deep Reinforcement Learning with Smooth Policy

21 Mar 2020Qianli ShenYan LiHaoming JiangZhaoran WangTuo Zhao

Deep neural networks have been widely adopted in modern reinforcement learning (RL) algorithms with great empirical successes in various domains. However, the large search space of training a neural network requires a significant amount of data, which makes the current RL algorithms not sample efficient... (read more)

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