2020
f-GAIL: Learning f-Divergence for Generative Adversarial Imitation Learning
NeurIPS 2020poster
Imitation learning (IL) aims to learn a policy from expert demonstrations that minimizes the discrepancy between the learner and expert behaviors. Various imitation learning algorithms have been proposed with different pre-determined divergences to quantify the discrepancy. This naturally gives rise…