Efficient Model-based Multi-agent Reinforcement Learning via Optimistic Equilibrium Computation

Pier Giuseppe Sessa, Maryam Kamgarpour, Andreas Krause

Abstract: We consider model-based multi-agent reinforcement learning, where the environment transition model is unknown and can only be learned via expensive interactions with the environment. We propose H-M...