Implementation of 'A Distributional Perspective on Reinforcement Learning' and 'Distributional Reinforcement Learning with Quantile Regression' based on OpenAi DQN baseline.
Install the OpenAi fork https://github.com/Silvicek/baselines (parent changes a lot, compatibility isn't guaranteed) Then install requirements
pip3 install -r requirements.txt
For simple benchmarking:
python3 train_[{cartpole, pong}].py
python3 enjoy_[{cartpole, pong}].py
For full Atari options see help
python3 train_atari.py --help
after learning, you can visualize the distributions by running
python3 enjoy_atari.py --visual ...
This implementation has been successfully tested on: Pong, Qbert, Seaquest
Some baseline features not supported (prioritized replay, double q-learning, dueling)