Reinforcement Learning and Deep RL Python Theory and Projects - Epsilon Greedy Strategy Implemented

The video tutorial covers the creation of an epsilon greedy strategy class in Python. It begins with initializing the class with start, end, and decay values. The tutorial then defines a function to calculate the exploration rate using a mathematical formula. The video concludes with a brief mention of the next steps, which involve creating an agent class.

How does the epsilon greedy strategy decide whether to explore or exploit?

What will be created in the upcoming video related to the epsilon greedy strategy?