Data-Driven Network LQG Mean Field Games with Heterogeneous Populations via Integral Reinforcement Learning

This paper establishes a data-driven solution for infinite horizon linear quadratic Gaussian Mean Field Games with network-coupled heterogeneous agent populations where the dynamics of the agents are unknown. The solution technique relies on Integral Reinforcement Learning and Kleinman's iteration f