A collection of Jupyter Notebook scripts used to demonstrate reinforcement learning (RL). Open each notebook (either locally or with Google Colab) and execute each of the cells. Note that if you are executing locally, you will need to install PyTorch.
To get started with RL, please watch the following video:
The video walks through the cartpole notebook. At the end, viewers are encouraged to modify that notebook to solve the inverted pendulum problem. I highly recommend trying this on your own before looking at my solution in the pendulum notebook.
A discussion of the pendulum solution can be found here %%%LINK%%%.
All code, unless otherwise noted, is licensed under the Zero-Clause BSD (0BSD) license.
Permission to use, copy, modify, and/or distribute this software for any purpose with or without fee is hereby granted.
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT, INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.