A Primer on Maximum Causal Entropy Inverse Reinforcement Learning [article]

Adam Gleave, Sam Toyer
2022 arXiv   pre-print
Inverse Reinforcement Learning (IRL) algorithms infer a reward function that explains demonstrations provided by an expert acting in the environment. Maximum Causal Entropy (MCE) IRL is currently the most popular formulation of IRL, with numerous extensions. In this tutorial, we present a compressed derivation of MCE IRL and the key results from contemporary implementations of MCE IRL algorithms. We hope this will serve both as an introductory resource for those new to the field, and as a
more » ... e reference for those already familiar with these topics.
arXiv:2203.11409v1 fatcat:gpcbomxf3nbbzkhkiw6uzqm36u