Learning Robust Reward Machines from Noisy Labels

Roko Parac, Lorenzo Nodari, Leo Ardon +3

This paper presents PROB-IRM, an approach that learns robust reward machines (RMs) for reinforcement learning (RL) agents from noisy execution traces. The key aspect of RM-driven R…