Reinforcement Learning — Teaching the Machine to Gamble — Q-learning

Reinforcement Learning is an area of ​​Artificial Intelligence and Machine Learning that involves simulating many scenarios in order to optimize the outcomes. One of the most used approaches in Reinforcement Learning is the Q-learning method. In Q-learning, a simulation environment is created and the algorithm involves a set of ‘S’ states for each simulating scenario, a set of ‘A’ actions, and an agent that takes these actions to permeate through the states.