This repository contains a PyTorch implementation of Monte Carlo policy gradient reinforcement (REINFORCE) for discrete action spaces.
🚧 🛠️👷♀️ 🛑 Under construction...
Install the required dependencies using the following command:
pip install -r requirements.txt
You can run the algorithm on any supported Gymnasium environment. For example:
python main.py --env 'LunarLander-v2'
CartPole-v1 |
MountainCar-v0 |
Acrobot-v1 |
LunarLander-v2 |
Asteroids-v5 |
Breakout-v5 |
BeamRider-v5 |
Centipede-v5 |
DonkeyKong-v5 |
Frogger-v5 |
KungFuMaster-v5 |
MarioBros-v5 |
SpaceInvaders-v5 |
Tetris-v5 |
Gopher-v5 |
MsPacman-v5 |
Pong-v5 |
Seaquest-v5 |
Special thanks to Phil Tabor, an excellent teacher! I highly recommend his Youtube channel.