Metadata-Version: 2.1
Name: Axelrod
Version: 4.10.0
Summary: Reproduce the Axelrod iterated prisoners dilemma tournament
Home-page: http://axelrod.readthedocs.org/
Author: Vince Knight, Owen Campbell, Karol Langner, Marc Harper
Author-email: axelrod-python@googlegroups.com
License: The MIT License (MIT)
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        Axelrod
        =======
        
        Goals
        -----
        
        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.
        
        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 an `infinite
          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 and `morality 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>`_
        
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Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3 :: Only
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
