Giorgio Manganini

Balancing Sample Efficiency and Suboptimality in Inverse Reinforcement Learning

We propose a novel formulation for the Inverse Reinforcement Learning (IRL) problem, which jointly accounts for the compatibility with the expert behavior of the identified reward and its effectiveness for the subsequent forward learning phase. Albeit quite natural, especially when the final goal is…