Reinforcement Learning is a type of machine learning that allows machines and software agents to maximize performance by learning from their environment. As new information enters a system, the reinforcement algorithms can re-evaluate their present state and choose a best line of action. This new information could reinforce the current state, or initiate a transform to a more ideal state. Eventually, reinforcement algorithms will approach and possibly converge upon the global optimum.