<commit_before>=================
rr.opt.mcts.basic
=================

A pure-Python toy implementation of Monte Carlo tree search. This simple version can be used to get a basic understanding of the algorithm and do some small experiments. When you feel comfortable, you should check out the full-blown implementation ``rr.opt.mcts.full``, which has many more features.


Python compatibility
--------------------

Compatible with Python 2.7+ and 3.5+ (thanks to the ``future`` library). The code may or may not work under earlier versions of Python 3 (perhaps back to 3.3).


Installation
------------

.. code-block:: bash

    git clone https://github.com/2xR/rr.opt.mcts.basic.git
    pip install ./rr.opt.mcts.basic


Contributing
------------

Contributions are welcome through github pull requests (tests would sure be nice to have... :P).

And if you're using the library and would like to say *"thanks!"* and/or keep me working on it, why not `buy me a beer <https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=2UMJC8HSU8RFJ&lc=PT&item_name=DoubleR&item_number=github%2f2xR%2fpaypal&currency_code=EUR&bn=PP%2dDonationsBF%3abtn_donate_LG%2egif%3aNonHosted>`_?<commit_msg>Add instructions for virtualenv installation<commit_after>=================
rr.opt.mcts.basic
=================

A pure-Python toy implementation of Monte Carlo tree search. This simple version can be used to get a basic understanding of the algorithm and do some small experiments. When you feel comfortable, you should check out the full-blown implementation ``rr.opt.mcts.full``, which has many more features.


Python compatibility
--------------------

Compatible with Python 2.7+ and 3.5+ (thanks to the ``future`` library). The code may or may not work under earlier versions of Python 3 (perhaps back to 3.3).


Installation
------------

.. code-block:: bash

    git clone https://github.com/2xR/rr.opt.mcts.basic.git
    pip install ./rr.opt.mcts.basic


In order to avoid polluting your system's Python installation, we recommend creating and installing into a `virtualenv <https://virtualenv.pypa.io/en/stable/>`_ with the following steps:

.. code-block:: bash

    git clone https://github.com/2xR/rr.opt.mcts.basic.git
    virtualenv venv
    source venv/bin/activate  # venv\Scripts\activate on Windows
    pip install ./rr.opt.mcts.basic


Contributing
------------

Contributions are welcome through github pull requests (tests would sure be nice to have... :P).

And if you're using the library and would like to say *"thanks!"* and/or keep me working on it, why not `buy me a beer <https://www.paypal.com/cgi-bin/webscr?cmd=_donations&business=2UMJC8HSU8RFJ&lc=PT&item_name=DoubleR&item_number=github%2f2xR%2fpaypal&currency_code=EUR&bn=PP%2dDonationsBF%3abtn_donate_LG%2egif%3aNonHosted>`_?
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