Numerical Methods for Finite-State Mean-Field Games Satisfying a Monotonicity Condition

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Abstract

Here, we develop numerical methods for finite-state mean-field games (MFGs) that satisfy a monotonicity condition. MFGs are determined by a system of differential equations with initial and terminal boundary conditions. These non-standard conditions make the numerical approximation of MFGs difficult. Using the monotonicity condition, we build a flow that is a contraction and whose fixed points solve both for stationary and time-dependent MFGs. We illustrate our methods with a MFG that models the paradigm-shift problem.

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Gomes, D. A., & Saúde, J. (2021). Numerical Methods for Finite-State Mean-Field Games Satisfying a Monotonicity Condition. Applied Mathematics and Optimization, 83(1), 51–82. https://doi.org/10.1007/s00245-018-9510-0

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