Better Exploration with Optimistic Actor-Critic

28 Oct 2019Kamil CiosekQuan VuongRobert LoftinKatja Hofmann

Actor-critic methods, a type of model-free Reinforcement Learning, have been successfully applied to challenging tasks in continuous control, often achieving state-of-the art performance. However, wide-scale adoption of these methods in real-world domains is made difficult by their poor sample efficiency... (read more)

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