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Reinforcement learning is an area of machine learning which addresses how an autonomous agent can learn long-term successful behavior through interaction with its environment. The term reinforcement learning has its roots in behavioral psychology, in particular to Pavlovian models of reward learning in animals. The modern theory of reinforcement learning, however, is much more influenced by mathematical theories of optimal control in operations research, such as dynamic programming.