Calculus of Variations and Geometric Measure Theory

M. Bardi - F. S. Priuli

LQG Mean-Field Games with ergodic cost

created by bardi on 08 Aug 2013
modified on 08 Jan 2014


Published Paper

Inserted: 8 aug 2013
Last Updated: 8 jan 2014

Journal: Proc. 52nd IEEE Conference on Decision and Control, Florence
Pages: 2493--2498
Year: 2013


We consider stochastic differential games with $N$ players, linear-Gaussian dynamics in arbitrary state-space dimension, and long-time-average cost with quadratic running cost. Admissible controls are feedbacks for which the system is ergodic. We first study the existence of affine Nash equilibria by means of an associated system of $N$ Hamilton-Jacobi-Bellman and $N$ Kolmogorov-Fokker-Planck partial differential equations. We give necessary and sufficient conditions for the existence and uniqueness of quadratic-Gaussian solutions in terms of the solvability of suitable algebraic Riccati and Sylvester equations. Under a symmetry condition on the running costs and for nearly identical players we study the large population limit, $N$ tending to infinity, and find a unique quadratic-Gaussian solution of the pair of Mean Field Game HJB-KFP equations. This extends some of the classical results on Mean Field Games by Huang, Caines, and Malhame and by Lasry and Lions, and the more recent paper by one of the authors in the 1-dimensional case.