MIT Institute for Data, Systems, and Society; University of California, Los Angeles; University of Copenhagen; University of Southern California; University of California, San Diego
Tiancheng Jin, Junyan Liu, Chloé Rouyer, William Chang, Chen-Yu Wei, Haipeng Luo
reinforcement Learning;best of both worlds;MDP;robust RL;adversarial corruption
No-Regret Online Reinforcement Learning with Adversarial Losses and Transitions