most citedDomain Adaptation In Reinforcement Learning Via Latent Unified State Representation

5 citations · 5 across the 1 of their papers we have counts for

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1 paper

cs.LG2021★ 5 cited

Domain Adaptation In Reinforcement Learning Via Latent Unified State Representation

Jinwei Xing, Takashi Nagata, Kexin Chen +3

Despite the recent success of deep reinforcement learning (RL), domain adaptation remains an open problem. Although the generalization ability of RL agents is critical for the real…