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What is: Primal Wasserstein Imitation Learning?

SourcePrimal Wasserstein Imitation Learning
Year2000
Data SourceCC BY-SA - https://paperswithcode.com

Primal Wasserstein Imitation Learning, or PWIL, is a method for imitation learning which ties to the primal form of the Wasserstein distance between the expert and the agent state-action distributions. The reward function is derived offline, as opposed to recent adversarial IL algorithms that learn a reward function through interactions with the environment, and requires little fine-tuning.