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Reinforcement learning

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Reinforcement learning Reinforcement learning is a type of machine learning that focuses on training algorithms to make decisions in a dynamic environment. Unlike supervised learning, in which the algorithm is given the correct output for each example in the training data, reinforcement learning algorithms must learn through trial and error, receiving feedback in the form of rewards or punishments for their actions.