Statistics, Linear Algebra, Probability, and Calculus are the four essential ideas that drive machine learning. While statistical ideas are essential to all models, calculus allows us to understand and optimize them.
However, there should be a lot of thought put into the feature/reward design. The pace of learning can be influenced by a variety of factors. Partially observable surroundings in realistic situations are possible. Too much Reinforcement may result in an overload of states, which can reduce the effectiveness of the outcomes.