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Project Description

DeeR

DeeR is a python library for Deep Reinforcement. It is build with modularity in mind so that it can easily be adapted to any need. It provides many possibilities out of the box (prioritized experience replay, double Q-learning, DDPG, etc). Many different environment examples are also provided (some of them using OpenAI gym).

Dependencies

This framework is tested to work under Python 2.7, and Python 3.5. It should also work with Python 3.3 and 3.4.

The required dependencies are NumPy >= 1.10, joblib >= 0.9. You also need theano >= 0.8 or tensorflow >= 0.9 along with the keras library.

For running the examples, Matplotlib >= 1.1.1 is required. For running the atari games environment, you need to install ALE >= 0.4.

Full Documentation

The documentation is available at : http://deer.readthedocs.io/en/master/

Here are a few examples :

Release History

Release History

0.3

This version

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0.3.dev1

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0.2.4

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0.2

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Changelog content for this version goes here.

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0.1

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TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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File Name & Checksum SHA256 Checksum Help Version File Type Upload Date
deer-0.3-py2-none-any.whl (166.2 kB) Copy SHA256 Checksum SHA256 py2 Wheel Nov 2, 2016
deer-0.3.tar.gz (64.4 kB) Copy SHA256 Checksum SHA256 Source Nov 2, 2016

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