Reinforcement Learning Pdf

Edition:
Release: 1998-03-01
Publisher: A Bradford Book
Binding: Hardcover
ISBN/ASIN: 0262193981



Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning)

Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives when interacting with a complex, uncertain environment. Free download Reinforcement Learning books collection in PDF, EPUB, FB2, MOBI, and TXT formats. In Reinforcement Learning, Richard Sutton and Andrew Barto 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 developments and applications. The only necessary mathematical background is familiarity with elementary concepts of probability.The book is divided into three parts. Best deals ebooks download Reinforcement Learning on amazon.Part I defines the reinforcement learning problem in terms of Markov decision processes. Part II provides basic solution methods: dynamic programming, Monte Carlo methods, and temporal-difference learning. Part III presents a unified view of the solution methods and incorporates artificial neural networks, eligibility traces, and planning; the two final chapters present case studies and consider the future of reinforcement learning. Reinforcement Learning: An Introduction (Adaptive Computation and Machine Learning) with free ebook downloads available via rapidshare, mediafire, 4shared, and hotfile.

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