MountainCar-v0
Reinforcement Learning algorithm to solve MountainCar-v0 in OpenAI gym. It uses the DDQN agent by tf-agents library
Set up
The environment is created and run in a docker container. To create the docker image with all requirements, you can run
make docker
Running the environment
To run the environment you can exec into the container and the run the files. To mount the working environment and open the bash inside the container you can run
make exec
Train the model
The training loop is in the file MountainCar-v0.py. To run it you can just use
the command
python3 MountainCar-v0.py
Visualize
To create a graph of the average evaluation reward over time you can run
python3 visualization.py