Curti Gabriele

Sub-optimal Experts mitigate Ambiguity in Inverse Reinforcement Learning

Inverse Reinforcement Learning (IRL) deals with the problem of deducing a reward function that explains the behavior of an expert agent who is assumed to act *optimally* in an underlying unknown task. Recent works have studied the IRL problem from the perspective of recovering the *feasible reward s…