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arXiv · 2008.05660

Imitating Unknown Policies via Exploration

Nathan Gavenski·Juarez Monteiro·Roger Granada·Felipe Meneguzzi·Rodrigo C. Barros
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Abstract

Behavioral cloning is an imitation learning technique that teaches an agent how to behave through expert demonstrations. Recent approaches use self-supervision of fully-observable unlabeled snapshots of the states to decode state-pairs into actions. However, the iterative learning scheme from these techniques are prone to getting stuck into bad local minima. We address these limitations incorporating a two-phase model into the original framework, which learns from unlabeled observations via exploration, substantially improving traditional behavioral cloning by exploiting (i) a sampling mechanism to prevent bad local minima, (ii) a sampling mechanism to improve exploration, and (iii) self-attention modules to capture global features. The resulting technique outperforms the previous state-of-the-art in four different environments by a large margin.

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Nathan Gavenski, Juarez Monteiro, Roger Granada, Felipe Meneguzzi, Rodrigo C. Barros. 2020-08-13. Imitating Unknown Policies via Exploration. https://arxiv.org/abs/2008.05660

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