Learning equilibria in Cournot mean field games of controls

Fuente: arXiv
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Main Authors: Camilli, Fabio, Laurière, Mathieu, Tang, Qing
Format: Preprint
Published: 2024
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author Camilli, Fabio
Laurière, Mathieu
Tang, Qing
author_facet Camilli, Fabio
Laurière, Mathieu
Tang, Qing
contents We consider Cournot mean field games of controls, a model originally developed for the production of an exhaustible resource by a continuum of producers. We prove uniqueness of the solution under general assumptions on the price function. Then, we prove convergence of a learning algorithm which gives existence of a solution to the mean field games system. The learning algorithm is implemented with a suitable finite difference discretization to get a numerical method to the solution. We supplement our theoretical analysis with several numerical examples and illustrate the impacts of model parameters.
format Preprint
id arxiv_https___arxiv_org_abs_2405_01812
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Learning equilibria in Cournot mean field games of controls
Camilli, Fabio
Laurière, Mathieu
Tang, Qing
Optimization and Control
Analysis of PDEs
We consider Cournot mean field games of controls, a model originally developed for the production of an exhaustible resource by a continuum of producers. We prove uniqueness of the solution under general assumptions on the price function. Then, we prove convergence of a learning algorithm which gives existence of a solution to the mean field games system. The learning algorithm is implemented with a suitable finite difference discretization to get a numerical method to the solution. We supplement our theoretical analysis with several numerical examples and illustrate the impacts of model parameters.
title Learning equilibria in Cournot mean field games of controls
topic Optimization and Control
Analysis of PDEs
url https://arxiv.org/abs/2405.01812