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An ideal machine is like a child’s brain, that can remember each and every decision taken in given tasks. In Reinforcement Learning, the learner isn’t told which action to take, but is instead made to try and discover actions that would yield maximum reward. In the most interesting and challenging cases, actions may not only affect the immediate reward, but also impact the next situation and all subsequent rewards. There are numerous application areas where machines have already proven their capability to outsmart humans.