Hyper-Meta Reinforcement Learning with Sparse Reward

11 Feb 2020Yun HuaXiangfeng WangBo JinWenhao LiJunchi YanXiaofeng HeHongyuan Zha

Despite their success, existing meta reinforcement learning methods still have difficulty in learning a meta policy effectively for RL problems with sparse reward. To this end, we develop a novel meta reinforcement learning framework, Hyper-Meta RL (HMRL), for sparse reward RL problems... (read more)

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