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

This is a library with simple dependencies (it only requires numpy) so that it is pip installable: if you want to do sophisticated equilibria computation YOU SHOULD use gambit.

This is a linear algebraic implementation of support enumeration using numpy.

This algorithm has also been implemented in Sagemath.

Installation

The easiest way to install is from pypi:

$ pip install nashpy  # This doesn't work yet  #TODO Speak to James

Usage

You can create a zero sum game by passing a single 2 dimensional array/list:

>>> import nash
>>> A = [[1, -1], [-1, 1]]
>>> matching_pennies = nash.Game(A)
>>> matching_pennies.zero_sum
True

To compute the equilibria you can iterate over Game.equilibria() which is a generator:

>>> for eq in matching_pennies.equilibria():
...     print(eq)
(array([ 0.5,  0.5]), array([ 0.5,  0.5]))

You can also create bi matrix games by passing two 2 dimensional arrays/lists:

>>> A = [[1, 2], [3, 0]]
>>> B = [[0, 2], [3, 1]]
>>> battle_of_the_sexes = nash.Game(A, B)
>>> battle_of_the_sexes.zero_sum
False
>>> for eq in battle_of_the_sexes.equilibria():
...     print(eq)
(array([ 1.,  0.]), array([ 0.,  1.]))
(array([ 0.,  1.]), array([ 1.,  0.]))
(array([ 0.5,  0.5]), array([ 0.5,  0.5]))

Development

To run the full test suite:

$ python setup.py test

All contributions are welcome, although this is meant to be a simple library, for more detailed game theoretic contribution please see gambit.