Reinforcement Learning 2025 pdf epub mobi 電子書下載

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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. 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. 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 2025 pdf epub mobi 電子書下載

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Reinforcement Learning 2025 pdf epub mobi 電子書下載

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http://incompleteideas.net/book/the-book-2nd.html 有第二版的 PDF(http://incompleteideas.net/book/bookdraft2018jan1.pdf) ，還有 Python 實現(https://github.com/ShangtongZhang/reinforcement-learning-an-introduction)。

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可以在綫閱讀，還不錯的我還沒仔細讀，先把網址公布齣來，大傢一起學習 http://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html

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可以在綫閱讀，還不錯的我還沒仔細讀，先把網址公布齣來，大傢一起學習 http://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html

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出版者:The MIT Press

作者:Richard S. Sutton

出品人:

頁數:342

譯者:

出版時間:1998-03-01

價格:USD 60.00