First information about setting up this repository can be found in our readme. This wiki contains tutorials and some additional tips and tricks. Take a look at the tutorials below!
The most common use case for a researcher is probably to extend an existing algorithm with a new feature or mechanism. This is covered in the tutorial to create a copy of SAC and start modifying it.
Tutorials
How to configure Pycharm for this project.
How to run a standard algorithm(SAC with Hindsight Experience Replay from stable baselines 3) and interpret the console output. This is also a good starting point for checking out other tutorials.
How to visualize and render.
How to manage hyperparameters and arguments with Hydra.
How to log data.
How to display logged data in MLFlow and Weights and Biases.
How to restore a saved policy.
How to set early stopping values.
As an example of how to create a new different algorithm from an existing one, we create a copy of SAC and start modifying it.
How to perform hyperparameter optimization.
How to set up and perform a performance test.
How to set up and perform a smoke test.
How to add a new robotic environment.
Further information
We created an overview over our custom environments.
Tips for training on remote computers.
Advice on running on Windows with WSL2.
How our GitLab pipeline works.