Pierluigi Vito Amadori

Random Expert Distillation: Imitation Learning via Expert Policy Support Estimation

We consider the problem of imitation learning from a finite set of expert trajectories, without access to reinforcement signals. The classical approach of extracting the expert’s reward function via inverse reinforcement learning, followed by reinforcement learning is indirect and may be computation…