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Displacement Convexity for First-Order Mean-Field Games
Author(s) -
Tommaso Seneci
Publication year - 2018
Publication title -
cornell university
Language(s) - English
DOI - 10.25781/kaust-1oc2f
Subject(s) - convexity , a priori and a posteriori , degenerate energy levels , displacement (psychology) , mathematics , regular polygon , order (exchange) , class (philosophy) , coupling (piping) , field (mathematics) , mathematical optimization , computer science , pure mathematics , geometry , physics , artificial intelligence , engineering , mechanical engineering , psychology , philosophy , epistemology , finance , quantum mechanics , financial economics , economics , psychotherapist
Here, we consider the planning problem for first-order mean-field games (MFG). When there is no coupling between players, MFG degenerate into optimal transport problems. Displacement convexity is a fundamental tool in optimal transport that often reveals hidden convexity of functionals and, thus, has numerous applications in the calculus of variations. We explore the similarities between the Benamou-Brenier formulation of optimal transport and MFG to extend displacement convexity methods from to MFG. In particular, we identify a class of functions, that depend on solutions of MFG, that are convex in time and, thus, obtain new a priori bounds for solutions of MFG. A remarkable consequence is the log-convexity of L norms. This convexity gives bounds for the density of solutions of the planning problem and extends displacement convexity of L norms from optimal transport. Additionally, we prove the convexity of L norms for MFG with congestion.

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