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Reinforcement Learning is a type of artificial intelligence (AI) that involves learning through trial-and-error. It has been used to achieve impressive results in a wide range of applications, from game playing to robotics. Reinforcement Learning is based on the idea of an agent interacting with an environment, observing the current state and taking an action that results in a reward signal. It has the advantage of learning from experience, but can be computationally expensive and prone to overfitting. Despite these challenges, Reinforcement Learning is an important tool in the AI toolkit and has enabled many of the recent breakthroughs in AI.