Log In Sign Up

A Simple Multiscale Method for Mean Field Games

by   Haoya Li, et al.

This paper proposes a multiscale method for solving the numerical solution of mean field games. Starting from an approximate solution at the coarsest level, the method constructs approximations on successively finer grids via alternating sweeping. At each level, numerical relaxation is used to stabilize the iterative process, and computing the initial guess by interpolating from the previous level accelerates the convergence. A second-order discretization scheme is derived for higher order convergence. Numerical examples are provided to demonstrate the efficiency of the proposed method.


page 10

page 13

page 14

page 16


On Numerical approximations of fractional and nonlocal Mean Field Games

We construct numerical approximations for Mean Field Games with fraction...

Error estimates of a theta-scheme for second-order mean field games

We introduce and analyze a new finite-difference scheme, relying on the ...

Mean-Field Learning: a Survey

In this paper we study iterative procedures for stationary equilibria in...

A Fictitious-play Finite-difference Method for Linearly Solvable Mean Field Games

A new numerical method for mean field games (MFGs) is proposed. The targ...

Exploration noise for learning linear-quadratic mean field games

The goal of this paper is to demonstrate that common noise may serve as ...

A high-order Lagrange-Galerkin scheme for a class of Fokker-Planck equations and applications to mean field games

In this paper we propose a high-order numerical scheme for linear Fokker...

An Iterative Decoupled Algorithm with Unconditional Stability for Biot Model

This paper is concerned with numerical algorithms for Biot model. By int...