Cross-Domain Imitation Learning with a Dual Structure

2 Jun 2020 Sungho Choi Seungyul Han Woojun Kim Youngchul Sung

In this paper, we consider cross-domain imitation learning (CDIL) in which an agent in a target domain learns a policy to perform well in the target domain by observing expert demonstrations in a source domain without accessing any reward function. In order to overcome the domain difference for imitation learning, we propose a dual-structured learning method... (read more)

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