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/.
翻译:Mean-Field Games(平均场博弈)是一种逼近 $N$-player games 的极限模型,具有许多应用。尽管计算 MFGs 的文献日益增多,但缺乏一种库,使得研究人员和实践者可以轻松地创建和解决自己的 MFG 问题。这篇论文的目的是介绍一个开源的 Python 库——MFGLib,其具有用户友好且可定制的接口,可用于解决通用 MFGs。它是创建和分析通用 MFG 环境的便捷工具,并嵌入了所有实现算法的自动调谐器。该软件包在 MIT 许可证下分发,源代码和文档可在 https://github.com/radar-research-lab/MFGLib/ 找到。