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Reinforcement learning, one of the most active research areas in Artificial Intelligence, is a computacional approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a coplex, uncertain environment. The authors provide a clear and simple account of the key ideas and algorithms of reinforcement learning. Their discussion ranges from the history of the field's intellectual foundations to the most recent development and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.