LQG Graphon Mean Field Games: Analysis via Graphon Invariant Subspaces
Abstract
This paper studies approximate solutions to large-scale linear quadratic stochastic games with homogeneous nodal dynamics parameters and heterogeneous network couplings within the graphon mean field game framework in [2]-[4]. A graphon time-varying dynamical system model is first formulated to study the finite and then limit problems of linear quadratic Gaussian graphon mean field games (LQG-GMFG). The Nash equilibrium of the limit problem is then characterized by two coupled graphon time-varying dynamical systems. Sufficient conditions are established for the existence of a unique solution to the limit LQG-GMFG problem. For the computation of LQG-GMFG solutions two methods are established and employed where one is based on fixed point iterations and the other on a decoupling operator Riccati equation; furthermore, two corresponding sets of solutions are established based on spectral decompositions. Finally, a set of numerical simulations on networks associated with different types of graphons are presented.
Cite
@article{arxiv.2004.00679,
title = {LQG Graphon Mean Field Games: Analysis via Graphon Invariant Subspaces},
author = {Shuang Gao and Peter E. Caines and Minyi Huang},
journal= {arXiv preprint arXiv:2004.00679},
year = {2021}
}