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Introduction to Reinforcement Learning

Introduction to Reinforcement Learning MAL Seminar 2014-2015 RL Background Learning by interacting with the environment Reward good behavior, punish bad behavior Trial & Error Combines ideas from psychology and control theory The Problem Reinforcement Learning is Learning what to do--how to map situations to actions--so as to maximize a numerical reward signal. The learner is not told which actions to take, as in most forms of machine Learning , but instead must discover which actions yield the most reward by trying them. In the most interesting and challenging cases, actions may affect not only the immediate reward but also the next situation and, through that, all subsequent rewards.

The Problem Reinforcement learning is learning what to do--how to map situations to actions--so as to maximize a numerical reward signal.The learner is not told which actions to take, as in most forms of machine learning, but instead

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