A Simple Multiscale Method for Mean Field Games
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.
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