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Reinforcement learning (RL, 강화 학습) is an area of Machine learning inspired by Behaviourist psychology, concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward. (https://en.wikipedia.org/wiki/Reinforcement_learning)

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