A mean field games model for finite mixtures of Bernoulli and categorical distributions

DOI10.3934/jdg.2020033zbMath1473.62208arXiv2004.08119OpenAlexW3112579469MaRDI QIDQ2246169

Laura Aquilanti, Simone Cacace, Fabio Camilli, Raul De Maio

Publication date: 16 November 2021

Published in: Journal of Dynamics and Games (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2004.08119

zbMATH Keywords

cluster analysisexpectation-maximization algorithmmixture modelsmean field gamesBernoulli distributioncategorical distribution

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Clustering in the social and behavioral sciences (91C20) Markov chains (discrete-time Markov processes on discrete state spaces) (60J10) Mean field games and control (49N80) Mean field games (aspects of game theory) (91A16)

Uses Software

• MNIST
• GitHub
• PRMLT

Cites Work

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• A mean-field optimal control formulation of deep learning
• Large population stochastic dynamic games: closed-loop McKean-Vlasov systems and the Nash certainty equivalence principle
• Mean field games models -- a brief survey
• Cluster Analysis
• On the Convergence of Policy Iteration in Stationary Dynamic Programming

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