scholarly journals Discrete-Time Ergodic Mean-Field Games with Average Reward on Compact Spaces

2019 ◽  
Vol 10 (1) ◽  
pp. 222-256
Author(s):  
Piotr Więcek
Author(s):  
Joseph Frédéric Bonnans ◽  
Pierre Lavigne ◽  
Laurent Pfeiffer

We propose and investigate a discrete-time mean field game model involving risk-averse agents. The model under study is a coupled system of dynamic programming equations with a Kolmogorov equation. The agents' risk aversion is modeled by composite risk measures. The existence of a solution to the coupled system is obtained with a fixed point approach. The corresponding feedback control allows to construct an approximate Nash equilibrium for a related dynamic game with finitely many players.


2015 ◽  
Vol 2 (1) ◽  
pp. 89-101
Author(s):  
Juan Pablo Maldonado López

Author(s):  
Piermarco Cannarsa ◽  
Wei Cheng ◽  
Cristian Mendico ◽  
Kaizhi Wang

AbstractWe study the asymptotic behavior of solutions to the constrained MFG system as the time horizon T goes to infinity. For this purpose, we analyze first Hamilton–Jacobi equations with state constraints from the viewpoint of weak KAM theory, constructing a Mather measure for the associated variational problem. Using these results, we show that a solution to the constrained ergodic mean field games system exists and the ergodic constant is unique. Finally, we prove that any solution of the first-order constrained MFG problem on [0, T] converges to the solution of the ergodic system as T goes to infinity.


Sign in / Sign up

Export Citation Format

Share Document