Reinforcement learning aims to create algorithms that can learn and adapt to environmental changes. This programming technique is based on the concept of receiving external stimuli that depend on the actions chosen by the agent. A correct choice will involve a reward, while an incorrect choice will lead to a penalty. The goal of the system is to achieve the best possible result, of course.
These mechanisms derive from the basic concepts of machine learning (ML) (learning from experience), in an attempt to simulate human behavior. In fact, in our mind, we activate brain mechanisms that lead us to chase and repeat what, in us, produce feelings of gratification and well-being. Whenever we experience moments of pleasure (for example, food, sex, and love), substances are produced in our brains that work by reinforcing that same stimulus, thus emphasizing...
