Canzhe Zhao

Logarithmic Regret for Linear Markov Decision Processes with Adversarial Corruptions

2025 · Proceedings of the AAAI Conference on Artificial Intelligence

In this work, we study the logarithmic regret for reinforcement learning (RL) with linear function approximation and adversarial corruptions, in the formulation of linear Markov decision processes (MDPs). Specifically, we consider the case where there …