Reinforcement Learning second edition Book [PDF] Download

Download the fantastic book titled Reinforcement Learning second edition written by Richard S. Sutton, available in its entirety in both PDF and EPUB formats for online reading. This page includes a concise summary, a preview of the book cover, and detailed information about "Reinforcement Learning second edition", which was released on 13 November 2018. We suggest perusing the summary before initiating your download. This book is a top selection for enthusiasts of the Computers genre.

Summary of Reinforcement Learning second edition by Richard S. Sutton PDF

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. 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 while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.


Detail About Reinforcement Learning second edition PDF

  • Author : Richard S. Sutton
  • Publisher : MIT Press
  • Genre : Computers
  • Total Pages : 549 pages
  • ISBN : 0262352702
  • PDF File Size : 39,7 Mb
  • Language : English
  • Rating : 4/5 from 21 reviews

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Reinforcement Learning, second edition

Reinforcement Learning, second edition
  • Publisher : MIT Press
  • File Size : 43,8 Mb
  • Release Date : 13 November 2018
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The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the

Deep Reinforcement Learning Hands-On

Deep Reinforcement Learning Hands-On
  • Publisher : Packt Publishing Ltd
  • File Size : 37,6 Mb
  • Release Date : 31 January 2020
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New edition of the bestselling guide to deep reinforcement learning and how it's used to solve complex real-world problems. Revised and expanded to include multi-agent methods, discrete optimization, RL in

Reinforcement Learning, second edition

Reinforcement Learning, second edition
  • Publisher : MIT Press
  • File Size : 41,5 Mb
  • Release Date : 13 November 2018
GET BOOK

The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the

Deep Reinforcement Learning Hands-On

Deep Reinforcement Learning Hands-On
  • Publisher : Packt Publishing Ltd
  • File Size : 47,7 Mb
  • Release Date : 21 June 2018
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This practical guide will teach you how deep learning (DL) can be used to solve complex real-world problems. Key Features Explore deep reinforcement learning (RL), from the first principles to

Foundations of Machine Learning, second edition

Foundations of Machine Learning, second edition
  • Publisher : MIT Press
  • File Size : 48,6 Mb
  • Release Date : 25 December 2018
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A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms. This book is a general introduction to machine learning that can serve

Reinforcement Learning

Reinforcement Learning
  • Publisher : "O'Reilly Media, Inc."
  • File Size : 33,9 Mb
  • Release Date : 06 November 2020
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Reinforcement learning (RL) will deliver one of the biggest breakthroughs in AI over the next decade, enabling algorithms to learn from their environment to achieve arbitrary goals. This exciting development

Deep Learning

Deep Learning
  • Publisher : MIT Press
  • File Size : 45,8 Mb
  • Release Date : 10 November 2016
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An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in

Machine Learning

Machine Learning
  • Publisher : CRC Press
  • File Size : 42,8 Mb
  • Release Date : 23 March 2011
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Traditional books on machine learning can be divided into two groups- those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how

Reinforcement Learning

Reinforcement Learning
  • Publisher : Springer Science & Business Media
  • File Size : 21,5 Mb
  • Release Date : 05 March 2012
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Reinforcement learning encompasses both a science of adaptive behavior of rational beings in uncertain environments and a computational methodology for finding optimal behaviors for challenging problems in control, optimization and

An Introduction to Statistical Learning

An Introduction to Statistical Learning
  • Publisher : Springer Nature
  • File Size : 31,9 Mb
  • Release Date : 01 August 2023
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An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have