Domain-Adversarial and -Conditional State Space Model for Imitation Learning

31 Jan 2020Ryo OkumuraMasashi OkadaTadahiro Taniguchi

State representation learning (SRL) in partially observable Markov decision processes has been studied to learn abstract features of data useful for robot control tasks. For SRL, acquiring domain-agnostic states is essential for achieving efficient imitation learning (IL)... (read more)

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