/ppo-pytorch

Proximal policy optimization in PyTorch. Easy to read and understand.

Primary LanguagePythonMIT LicenseMIT

Proximal Policy Optimization

I recommend using the original code https://github.com/ikostrikov/pytorch-a2c-ppo-acktr or my personal RL code base https://github.com/ASzot/rl-toolkit

Implementation of https://arxiv.org/abs/1707.06347 from OpenAI for continuous action spaces.

This implementation is designed to be simple and easy to read. No complicated logic or unnecessary Python magic.

Based on the code from https://github.com/ikostrikov/pytorch-a2c-ppo-acktr.

Usage

python train.py to train.

python evaluate.py to test.

Requirements

All you need are PyTorch, Gym, and possibly MuJoCo depending on what environment you want to run. For training you will also need tensorboard-pytorch installed.