Abstract:Abstract. Imitation learning is an effective strategy to reinforcement learning, which avoids the delayed reward problem by learning from mentor-demonstrated trajectories. A limitation for imitation learning is that collecting sufficient qualified demonstrations is quite expensive. In this work, we study how an agent can automatically improve its performance from a weak policy, by automatically acquiring more demonstrations for learning. We propose the LEWE framework to sample tasks for the weak policy to exec… Show more
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