Convergence of a model-free entropy-regularized inverse reinforcement learning algorithm

Titouan Renard, Andreas Schlaginhaufen, Tingting Ni +1

Given a dataset of expert demonstrations, inverse reinforcement learning (IRL) aims to recover a reward for which the expert is optimal. This work proposes a model-free algorithm t…