Simon created a wonderful project in Processing – a path finder that looks for the shortest path to reach the green cell, avoiding the obstacles. Every time the path finder fails, it tries again. Simon also built a counter for the number of tries. The next step is turning the grid into a game environment and training the path finder, Simon says, i.e. applying reinforcement learning. Simon thinks he should use the Q function in this stochastic environment, but is still very timid about its implementation. In the third video below, he explains how this project could help him take his first cautious steps in the direction of machine learning.