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A research tool for the Iterated Prisoner's Dilemma

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A Python library with the following principles and goals:

  1. Enabling the reproduction of previous Iterated Prisoner's Dilemma research as easily as possible.
  2. Creating the de-facto tool for future Iterated Prisoner's Dilemma research.
  3. Providing as simple a means as possible for anyone to define and contribute new and original Iterated Prisoner's Dilemma strategies.
  4. Emphasizing readability along with an open and welcoming community that is accommodating for developers and researchers of a variety of skill levels.


With Axelrod you:

  • have access
    to over 200 strategies
    _, including original and classics like Tit For Tat and Win Stay Lose Shift. These are extendable through parametrization and a collection of strategy transformers.
  • can create
    head to head matches
    _ between pairs of strategies.
  • can create
    _ over a number of strategies.
  • can study population dynamics through
    Moran processes
    _ and an
    population model
  • can analyse detailed
    results of tournaments
    _ and matches.
  • can
    visualise results
    _ of tournaments.

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  • can reproduce a number of contemporary research topics such as
    _ of strategies and
    morality metrics

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The library has 100% test coverage and is extensively documented. See the documentation for details and examples of all the features:

An open reproducible framework for the study of the iterated prisoner's
_: a peer reviewed paper introducing the library (22 authors).


The library is tested on Python versions 3.8, 3.9, and 3.10.

The simplest way to install is::

$ pip install axelrod

To install from source::

$ git clone
$ cd Axelrod
$ python install

Quick Start

The following runs a basic tournament::

>>> import axelrod as axl
>>> players = [s() for s in axl.demo_strategies]  # Create players
>>> tournament = axl.Tournament(players, seed=1)  # Create a tournament
>>> results =  # Play the tournament
>>> results.ranked_names
['Defector', 'Grudger', 'Tit For Tat', 'Cooperator', 'Random: 0.5']


  • is a tournament pitting all the strategies in the repository against each other. These results can be easily viewed at
  • contains a set of example Jupyter notebooks.
  • contains fingerprints (data and plots) of all strategies in the library.


All contributions are welcome!

You can find helpful instructions about contributing in the documentation:


You can find a list of publications that make use of or cite the library on the

_ page.


The library has had many awesome contributions from many

_. The Core developers of the project are:
  • drvinceknight 
  • gaffney2010 
  • marcharper 
  • meatballs 
  • nikoleta-v3 

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