English

Linear-Quadratic $N$-person and Mean-Field Games with Ergodic Cost

Analysis of PDEs 2014-07-10 v2 Optimization and Control

Abstract

We consider stochastic differential games with NN 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 NN Hamilton-Jacobi-Bellman and NN 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, NN tending to infinity, and find a unique quadratic-Gaussian solution of the pair of Mean Field Game HJB-KFP equations. Examples of explicit solutions are given, in particular for consensus problems.

Keywords

Cite

@article{arxiv.1401.1421,
  title  = {Linear-Quadratic $N$-person and Mean-Field Games with Ergodic Cost},
  author = {Martino Bardi and Fabio S. Priuli},
  journal= {arXiv preprint arXiv:1401.1421},
  year   = {2014}
}

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31 pages