Primal Wasserstein Imitation Learning

8 Jun 2020Robert DadashiLéonard HussenotMatthieu GeistOlivier Pietquin

Imitation Learning (IL) methods seek to match the behavior of an agent with that of an expert. In the present work, we propose a new IL method based on a conceptually simple algorithm: Primal Wasserstein Imitation Learning (PWIL), which ties to the primal form of the Wasserstein distance between the expert and the agent state-action distributions... (read more)

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