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Tutorials for reinforcement learning in PyTorch and Gym by implementing a few of the popular algorithms. [IN PROGRESS]

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PyTorch Reinforcement Learning

This repo contains tutorials covering reinforcement learning using PyTorch 1.3 and Gym 0.15.4 using Python 3.7.

If you find any mistakes or disagree with any of the explanations, please do not hesitate to submit an issue. I welcome any feedback, positive or negative!

Getting Started

To install PyTorch, see installation instructions on the PyTorch website.

To install Gym, see installation instructions on the Gym GitHub repo.

Tutorials

All tutorials use Monte Carlo methods to train the CartPole-v1 environment with the goal of reaching a total episode reward of 475 averaged over the last 25 episodes. There are also alternate versions of some algorithms to show how to use those algorithms with other environments.

Potential algorithms covered in future tutorials: DQN, ACER, ACKTR.

References