Reinforcement Learning (RL) is an area of machine learning concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward.
In machine learning, the environment is typically formulated as a Markov Decision Process, as many reinforcement learning algorithms for this context utilize dynamic programming techniques.
Learn more about Reinforcement Learning, Deep Reinforcement Learning and Deep Q-Leaning in our review of the MIT course on Deep Reinforcement Learning, or read more on Wikipedia.
« Back to Glossary Index