Toward Computationally Efficient Inverse Reinforcement Learning via Reward Shaping

no code implementations • 15 Dec 2023 • Lauren H. Cooke, Harvey Klyne, Edwin Zhang, Cassidy Laidlaw, Milind Tambe, Finale Doshi-Velez

Inverse reinforcement learning (IRL) is computationally challenging, with common approaches requiring the solution of multiple reinforcement learning (RL) sub-problems.

reinforcement-learning Reinforcement Learning (RL)