Reinforcement learning, a type of artificial intelligence that works through reward-based learning, has shown its potential by efficiently learning to play games like Atari and Chess, but can be applied to almost any digitized domain through trial and error learning. With the ability to learn for itself, and without any programmed rules, the possibilities for widespread application of reinforcement learning continue to increase.