The Unity Obstacle Tower Challenge was introduced in February 2019 as a discrete visual learning problem. As we have seen before, this is the holy grail of learning for games, robotics, and other simulations. What makes it more interesting is this challenge was introduced outside of ML-Agents and requires the challenger to write their own Python code from scratch to control the game—something we have come close to learning how to do in this book, but we omitted the technical details. Instead, we focused on the fundamentals of tuning hyperparameters, understanding rewards, and the agent state. All of these fundamentals will come in handy if you decide to tackle the tower challenge.
At the time this book was written, the ML-Agents version used for developing was 0.6. If you have run all the exercises to completion, you will have noticed...
