https://github.com/wilrop/ramo

Algorithms for computing or learning equilibria in multi-objective games
https://github.com/wilrop/ramo

algorithmic-game-theory game-theory multi-agent multi-objective reinforcement-learning

Last synced: 22 days ago
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Algorithms for computing or learning equilibria in multi-objective games

• Host: GitHub
• URL: https://github.com/wilrop/ramo
• Owner: wilrop
• License: mit
• Created: 2022-01-13T16:22:14.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2023-05-09T12:30:07.000Z (over 1 year ago)
• Last Synced: 2024-11-18T19:51:48.645Z (about 1 month ago)
• Topics: algorithmic-game-theory, game-theory, multi-agent, multi-objective, reinforcement-learning
• Language: Python
• Homepage: https://ramo.readthedocs.io/en/latest/
• Size: 363 KB
• Stars: 4
• Watchers: 2
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Ramo

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](https://ramo.readthedocs.io/en/latest/) for a complete overview of the framework and its capabilities.

## Installation

Installing Ramo is as easy as typing

````python

pip install ramo

````

If you would like to install from source, simply download this project as a zip file and place the folder at your desired location.

## Contributing

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 ([email protected]) so we can discuss how to move forward.

## Citation

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](references.md).

## License

This project is licensed under the terms of the MIT license.