This package implements the Generative Recurrent Neural Networks from the paper from Gupta et al. and combines it with the Reinforcement Learning procedures described in the paper from Olivecrona et al.

• Silvia Amabilino (NovaData Solutions ltd., University of Bristol)
• Michael Mazanetz (NovaData Solutions ltd.)
• David Glowacki (University of Bristol)

In order to use this package, you need the following packages installed:

• scikit-learn (0.19.1 or higher)
• tensorflow (1.9.0 or higher, but < tensorflow 2.0) or tensorflow-gpu (1.9.0 or higher, but < tensorflow 2.0)
• keras (2.2.0 or higher)
• rdkit (optional)

RDkit is only needed for the reward function in reinforcement learning.

To install, you can run the following command:

pip install git+https://github.com/SilviaAmAm/MolBot.git

Otherwise, you can clone the repository:

git clone https://github.com/SilviaAmAm/MolBot.git

and then, in your desired python environment, run:

cd MolBot
pip install MolBot/

To build the documentation, these packages are required:

• nbsphinx
• sphinx_rtd_theme

In the docs folder, run:

make html

Then, open ./docs/build/html/index.html.

You can have a look at some examples in the examples folder.

Go to the test directory:

cd tests

Then, run all the tests:

pytest test_*