Ethan Wang

Pessimism Meets Invariance: Provably Efficient Offline Mean-Field Multi-Agent RL

Mean-Field Multi-Agent Reinforcement Learning (MF-MARL) is attractive in the applications involving a large population of homogeneous agents, as it exploits the permutation invariance of agents and avoids the curse of many agents. Most existing results only focus on online settings, in which agents…