Metadata-Version: 2.0
Name: deer
Version: 0.1
Summary: Framework for deep reinforcement learning
Home-page: https://github.com/VinF/General_Deep_Q_RL
Author: Vincent Francois-Lavet
Author-email: v.francois@ulg.ac.be
License: BSD
Platform: any
Classifier: Development Status :: 3 - Alpha
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Utilities
Classifier: Topic :: Software Development :: Libraries

## Full Documentation

See the [Wiki](https://github.com/VinF/deer/wiki) for full documentation, examples and other information.

## 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 >= 0.7 (lasagne is optional) or you can write your own neural network using your favorite framework.

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

## How to install
You can simply clone the version 0.1 of this framework by using the following command:
```
git clone -b 0.1 https://github.com/VinF/deer.git
```
That version is not a package yet, so you can simply launch it as a standalone python code.


For the latest developments, you can instead clone the bleeding-edge version of this framework by using the following command:
```
git clone -b master https://github.com/VinF/deer.git
```

Assuming you already have a python environment with pip, you can automatically install all the dependencies (except ALE that you may need for atari games) with:
```
pip install -r requirements.txt
```

And you can install the framework as a package with:
```
python setup.py install
```


