KAUST DepartmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Applied Mathematics and Computational Science Program
Center for Uncertainty Quantification in Computational Science and Engineering (SRI-UQ)
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AbstractHere, we consider numerical methods for stationary mean-field games (MFG) and investigate two classes of algorithms. The first one is a gradient-flow method based on the variational characterization of certain MFG. The second one uses monotonicity properties of MFG. We illustrate our methods with various examples, including one-dimensional periodic MFG, congestion problems, and higher-dimensional models.
CitationAlmulla N, Ferreira R, Gomes D (2016) Two Numerical Approaches to Stationary Mean-Field Games. Dynamic Games and Applications 7: 657–682. Available: http://dx.doi.org/10.1007/s13235-016-0203-5.
SponsorsThe authors were partially supported by King Abdullah University of Science and Technology baseline and start-up funds and by KAUST SRI, Center for Uncertainty Quantification in Computational Science and Engineering.
JournalDynamic Games and Applications