Provable Benefits of Regularization: Fast Rates for Adversarial Imitation Learning

Hanbin Zhou, Shangzhe Li, Alexander Braverman +1

We study adversarial imitation learning (AIL), in which an agent learns to imitate expert demonstrations by optimizing a policy against an adversarial reward that distinguishes exp…