Axelrod-Python / Axelrod
Programming Languages
Projects that are alternatives of or similar to Axelrod
.. image:: https://img.shields.io/pypi/v/Axelrod.svg :target: https://pypi.python.org/pypi/Axelrod
.. image:: https://zenodo.org/badge/19509/Axelrod-Python/Axelrod.svg :target: https://zenodo.org/badge/latestdoi/19509/Axelrod-Python/Axelrod
.. image:: https://github.com/Axelrod-Python/Axelrod/workflows/CI/badge.svg :target: https://github.com/Axelrod-Python/Axelrod/actions
|Join the chat at https://gitter.im/Axelrod-Python/Axelrod|
Axelrod
Goals
A Python library with the following principles and goals:
- Enabling the reproduction of previous Iterated Prisoner's Dilemma research as easily as possible.
- Creating the de-facto tool for future Iterated Prisoner's Dilemma research.
- Providing as simple a means as possible for anyone to define and contribute new and original Iterated Prisoner's Dilemma strategies.
- Emphasizing readability along with an open and welcoming community that is accommodating for developers and researchers of a variety of skill levels.
Features
With Axelrod you:
-
have access
to over 200 strategies <http://axelrod.readthedocs.io/en/stable/reference/all_strategies.html>
_, 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 <http://axelrod.readthedocs.io/en/stable/tutorials/getting_started/match.html>
_ between pairs of strategies. -
can create
tournaments <http://axelrod.readthedocs.io/en/stable/tutorials/getting_started/tournament.html>
_ over a number of strategies. -
can study population dynamics through
Moran processes <http://axelrod.readthedocs.io/en/stable/tutorials/getting_started/moran.html>
_ and aninfinite population model <http://axelrod.readthedocs.io/en/stable/tutorials/further_topics/ecological_variant.html>
_. -
can analyse detailed
results of tournaments <http://axelrod.readthedocs.io/en/stable/tutorials/getting_started/summarising_tournaments.html>
_ and matches. -
can
visualise results <http://axelrod.readthedocs.io/en/stable/tutorials/getting_started/visualising_results.html>
_ of tournaments... image:: http://axelrod.readthedocs.io/en/stable/_images/demo_strategies_boxplot.svg :height: 300 px :align: center
-
can reproduce a number of contemporary research topics such as
fingerprinting <http://axelrod.readthedocs.io/en/stable/tutorials/further_topics/fingerprinting.html>
_ of strategies andmorality metrics <http://axelrod.readthedocs.io/en/stable/tutorials/further_topics/morality_metrics.html>
_... image:: https://github.com/Axelrod-Python/Axelrod-fingerprint/raw/master/assets/Tricky_Defector.png :height: 300 px :align: center
The library has 100% test coverage and is extensively documented. See the documentation for details and examples of all the features: http://axelrod.readthedocs.org/
An open reproducible framework for the study of the iterated prisoner's dilemma <http://openresearchsoftware.metajnl.com/article/10.5334/jors.125/>
_:
a peer reviewed paper introducing the library (22 authors).
Installation
The library requires Python 3.6 or greater.
The simplest way to install is::
$ pip install axelrod
To install from source::
$ git clone https://github.com/Axelrod-Python/Axelrod.git
$ cd Axelrod
$ python setup.py 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 = tournament.play() # Play the tournament
>>> results.ranked_names
['Defector', 'Grudger', 'Tit For Tat', 'Cooperator', 'Random: 0.5']
Examples
- https://github.com/Axelrod-Python/tournament is a tournament pitting all the strategies in the repository against each other. These results can be easily viewed at http://axelrod-tournament.readthedocs.org.
- https://github.com/Axelrod-Python/Axelrod-notebooks contains a set of example Jupyter notebooks.
- https://github.com/Axelrod-Python/Axelrod-fingerprint contains fingerprints (data and plots) of all strategies in the library.
Contributing
All contributions are welcome!
You can find helpful instructions about contributing in the documentation: http://axelrod.readthedocs.org/en/latest/tutorials/contributing/index.html
Publications
You can find a list of publications that make use of or cite the library
on the citations <https://github.com/Axelrod-Python/Axelrod/blob/master/citations.md>
_ page.
Contributors
The library has had many awesome contributions from many great contributors <https://github.com/Axelrod-Python/Axelrod/graphs/contributors>
_.
The Core developers of the project are:
-
drvinceknight <https://github.com/drvinceknight>
_ -
gaffney2010 <https://github.com/gaffney2010>
_ -
marcharper <https://github.com/marcharper>
_ -
meatballs <https://github.com/meatballs>
_ -
nikoleta-v3 <https://github.com/Nikoleta-v3>
_
.. |Join the chat at https://gitter.im/Axelrod-Python/Axelrod| image:: https://badges.gitter.im/Join%20Chat.svg :target: https://gitter.im/Axelrod-Python/Axelrod?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge