No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions

Tiancheng Jin, Junyan Liu, Chloé Rouyer +3

Existing online learning algorithms for adversarial Markov Decision Processes achieve $O(\sqrt{T})$ regret after $T$ rounds of interactions even if the loss functions are chosen…