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Hauptverfasser: Cont, Rama, Hu, Anran
Format: Preprint
Veröffentlicht: 2025
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Online-Zugang:https://arxiv.org/abs/2502.12389
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author Cont, Rama
Hu, Anran
author_facet Cont, Rama
Hu, Anran
contents We investigate how the framework of mean-field games may be used to investigate strategic interactions in large heterogeneous populations. We consider strategic interactions in a population of players which may be partitioned into near-homogeneous sub-populations subject to peer group effects and interactions across groups. We prove a quantitative homogenization result for multi-player games in this setting: we show that $ε$-Nash equilibria of a general multi-player game with heterogeneity may be computed in terms of the Nash equilibria of an auxiliary multi-population mean-field game. We provide explicit and non-asymptotic bounds for the distance from optimality in terms of the number of players and the deviations from homogeneity in sub-populations. The best mean-field approximation corresponds to an optimal partition into sub-populations, which may be formulated as the solution of a mixed-integer program.
format Preprint
id arxiv_https___arxiv_org_abs_2502_12389
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Homogenization and Mean-Field Approximation for Multi-Player Games
Cont, Rama
Hu, Anran
Optimization and Control
We investigate how the framework of mean-field games may be used to investigate strategic interactions in large heterogeneous populations. We consider strategic interactions in a population of players which may be partitioned into near-homogeneous sub-populations subject to peer group effects and interactions across groups. We prove a quantitative homogenization result for multi-player games in this setting: we show that $ε$-Nash equilibria of a general multi-player game with heterogeneity may be computed in terms of the Nash equilibria of an auxiliary multi-population mean-field game. We provide explicit and non-asymptotic bounds for the distance from optimality in terms of the number of players and the deviations from homogeneity in sub-populations. The best mean-field approximation corresponds to an optimal partition into sub-populations, which may be formulated as the solution of a mixed-integer program.
title Homogenization and Mean-Field Approximation for Multi-Player Games
topic Optimization and Control
url https://arxiv.org/abs/2502.12389