Reinforcement learning has software agents which take action in an environment to maximize cumulative rewards. It comes under the area of machine learning and it is one of the three basic machine learning paradigms along with supervised and unsupervised learning. It differs from supervised learning in the way that the training data has the answer key with it whereas in reinforcement learning, there is no answer but the reinforcement agent decides what to do to perform the given task.
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