BYU CS classes

• To implement the Proximal Policy Optimization algorithm

For this lab, you will turn in a colab notebook that implements the proximal policy optimization (PPO) algorithm.

Your notebook will be graded on the following:

• 40% Proper design, creation and debugging of a dense prediction network
• 40% Proper implementation of a loss function and train/test set accuracy measure
• 10% Tidy visualizations of loss of your dense predictor during training
• 10% Test image output

For this lab, you will implement the PPO algorithm, and train it on a few simple worlds.

Here is the paper with a technical description of the algorithm: Proximal policy optimization.

Here is a video describing it at a high level: PPO video