Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards

27 Jul 2017Mel VecerikTodd HesterJonathan ScholzFumin WangOlivier PietquinBilal PiotNicolas HeessThomas RothörlThomas LampeMartin Riedmiller

We propose a general and model-free approach for Reinforcement Learning (RL) on real robotics with sparse rewards. We build upon the Deep Deterministic Policy Gradient (DDPG) algorithm to use demonstrations... (read more)

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