Ramo is an algorithmic game theory framework offering a collection of algorithms and utilities for computing or learning (approximate) equilibria in multi-objective games.
Please visit Ramo's docs for a complete overview of the framework and its capabilities.
Installing Ramo is as easy as typing
pip install ramoIf you would like to install from source, simply download this project as a zip file and place the folder at your desired location.
We are building a library containing cutting edge research in multi-objective game theory. If you are working in this area and want to get involved, contributions are very welcome! Our focus is specifically on multi-objective games, but single-objective contributions are also welcome. If you are considering contributing, please send me a message (willem.ropke@vub.be) so we can discuss how to move forward.
To cite the usage of this repository please use the following:
@misc{ropke2022ramo,
author = {Willem Röpke},
title = {Ramo: Rational Agents with Multiple Objectives},
year = {2022},
publisher = {GitHub},
journal = {GitHub repository},
howpublished = {\url{https://github.com/wilrop/mo-game-theory}},
}
This repository contains (derivatives of) original work that has been published elsewhere. We present a complete overview of which algorithms come from which work in references.md.
This project is licensed under the terms of the MIT license.