Learning to Reach Goals via Iterated Supervised Learning

ICLR 2020 Dibya GhoshAbhishek GuptaAshwin ReddyJustin FuColine DevinBenjamin EysenbachSergey Levine

Current reinforcement learning (RL) algorithms can be brittle and difficult to use, especially when learning goal-reaching behaviors from sparse rewards. Although supervised imitation learning provides a simple and stable alternative, it requires access to demonstrations from a human supervisor... (read more)

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