PyTorch Implementation of the Maximum a Posteriori Policy Optimisation (paper1, paper2) Reinforcement Learning Algorithms for OpenAI gym environments.
I tested on the below environment.
- Windows 10
- Python 3.7
- PyTorch 1.8.1
Install PyTorch https://pytorch.org/
pip install gym Box2D IPython tqdm scipy tensorboard tensorboardx
python train.py \
--device cuda:0 \
--env LunarLanderContinuous-v2 \
--log log_continuous \
--render
python train.py \
--device cuda:0 \
--env LunarLander-v2 \
--log log_discrete \
--render
This repository is a clone of theogruner/rl_pro_telu, which is licensed under the GNU GPL3 License - see the LICENSE file for details