This is a reinforcement learning framework made with research activity in mind. You can read mode about PRL in our introductory blog post, in-depth look into library, documentation or wiki.
python 3.6
swig
python3-dev
We recommend using virtualenv
for installing project dependencies.
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clone the project:
git clone [email protected]:opium-sh/prl.git
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create and activate a virtualenv for the project (you can skip this step if you are not using virtualenv)
virtualenv -p python3.6 your/path && source your/path/bin/activate
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install dependencies:
pip install -r requirements.txt
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install library
pip install -e .
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run example:
cd examples python cart_pole_example_cross_entropy.py
If you use PRL in your work or research please cite us as:
Tempczyk, P., Sliwowski, M., Kozakowski, P., Smuda, P., Topolski, B., Nabrdalik, F., & Malisz, T. (2020). opium-sh/prl: First release of Peoples’s Reinforcement Learning (PRL). Zenodo. https://doi.org/10.5281/ZENODO.3662113