Decentralized Multi-Agents by Imitation of a Centralized Controller

Alex Tong Lin, Mark J. Debord, Katia Estabridis, Gary A. Hewer, Guido Montúfar, Stanley J. Osher

Abstract: We consider a multi-agent reinforcement learning problem where each agent seeks to maximize a shared reward while interacting with other agents, and they may or may not be able to communicate. Typi...