This repository contains the code required to reproduce the results in the paper "Coordinating Planning and Tracking in Layered Control Policies via Actor-Critic Learning" by F. Yang and N. Matni.
The notebooks/ folder contains a notebook that illustrates how to use this
codebase. The experiment scripts are contained inside the experiments folder,
with the exception of the unicycle system, which is in the notebook. After
running the notebook or an experiment script, a runs/ folder will be created
inside the script directory, which contains the training logs. These training
info can be visualized and read off by running tensorboard --logdir {directory_name}/run/.