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A library to compute equilibria of 2 player normal form games

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Nashpy: a python library for the computation of equilibria of 2 player strategic games.

This library implements the following algorithms for Nash equilibria on 2 player games:

  • Support enumeration
  • Best response polytope vertex enumeration
  • Lemke Howson algorithm

Nashpy has a small set of Python dependencies: it only requires numpy and scipy so is straightforward to install on all operating systems.

Installation

$ python -m pip install nashpy

To install Nashpy on Fedora, use:

$ dnf install python3-nashpy

Usage

Create bi matrix games by passing two 2 dimensional arrays/lists:

>>> import nashpy as nash
>>> A = [[1, 2], [3, 0]]
>>> B = [[0, 2], [3, 1]]
>>> game = nash.Game(A, B)
>>> for eq in game.support_enumeration():
...     print(eq)
(array([1., 0.]), array([0., 1.]))
(array([0., 1.]), array([1., 0.]))
(array([0.5, 0.5]), array([0.5, 0.5]))
>>> game[[0, 1], [1, 0]]
array([3, 3])

Documentation

Full documentation is available here: http://nashpy.readthedocs.io/

Other game theoretic software

  • Gambit is a library with a python api and support for more algorithms and more than 2 player games.
  • Game theory explorer a web interface to gambit useful for teaching.
  • Axelrod a research library aimed at the study of the Iterated Prisoners dilemma

Development

Clone the repository and create a virtual environment:

$ git clone https://github.com/drvinceknight/nashpy.git
$ cd nashpy
$ python -m venv env

Activate the virtual environment and install tox:

$ source env/bin/activate
$ python -m pip install tox

Make modifications.

To run the tests:

$ python -m tox

To build the documentation. First install the software which also installs the documentation build requirements.

$ python -m pip install flit
$ python -m flit install --symlink

Then:

$ cd docs
$ make html

Full contribution documentation is available at https://nashpy.readthedocs.io/en/latest/contributing/index.html

Pull requests are welcome.

Code of conduct

In the interest of fostering an open and welcoming environment, all contributors, maintainers and users are expected to abide by the Python code of conduct: https://www.python.org/psf/codeofconduct/

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