MFGLib: A Library for Mean-Field Games

Fuente: arXiv
Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Guo, Xin, Hu, Anran, Santamaria, Matteo, Tajrobehkar, Mahan, Zhang, Junzi
Format: Preprint
Veröffentlicht: 2023
Schlagworte:
Online-Zugang:
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
_version_ 1866916930307227648
author Guo, Xin
Hu, Anran
Santamaria, Matteo
Tajrobehkar, Mahan
Zhang, Junzi
author_facet Guo, Xin
Hu, Anran
Santamaria, Matteo
Tajrobehkar, Mahan
Zhang, Junzi
contents Mean-field games (MFGs) are limiting models to approximate $N$-player games, with a number of applications. Despite the ever-growing numerical literature on computation of MFGs, there is no library that allows researchers and practitioners to easily create and solve their own MFG problems. The purpose of this document is to introduce MFGLib, an open-source Python library for solving general MFGs with a user-friendly and customizable interface. It serves as a handy tool for creating and analyzing generic MFG environments, along with embedded auto-tuners for all implemented algorithms. The package is distributed under the MIT license and the source code and documentation can be found at https://github.com/radar-research-lab/MFGLib/.
format Preprint
id arxiv_https___arxiv_org_abs_2304_08630
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle MFGLib: A Library for Mean-Field Games
Guo, Xin
Hu, Anran
Santamaria, Matteo
Tajrobehkar, Mahan
Zhang, Junzi
Computer Science and Game Theory
Mean-field games (MFGs) are limiting models to approximate $N$-player games, with a number of applications. Despite the ever-growing numerical literature on computation of MFGs, there is no library that allows researchers and practitioners to easily create and solve their own MFG problems. The purpose of this document is to introduce MFGLib, an open-source Python library for solving general MFGs with a user-friendly and customizable interface. It serves as a handy tool for creating and analyzing generic MFG environments, along with embedded auto-tuners for all implemented algorithms. The package is distributed under the MIT license and the source code and documentation can be found at https://github.com/radar-research-lab/MFGLib/.
title MFGLib: A Library for Mean-Field Games
topic Computer Science and Game Theory
url https://arxiv.org/abs/2304.08630