Provably Efficient Q-learning for Robust Reinforcement Learning.

arXiv:2610.35656v1 Announce Type: cross Abstract: Standard reinforcement learning (RL) algorithms based on Markov Decision Processes (MDPs) are vulnerable to sim-to-real gaps. To address this issue, distributionally robust RL algorithms based on robust MDPs (R