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Adaptive Computation and Machine Learning Ser.: Reinforcement Learning,...

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Last updated on Feb 08, 2025 08:34:06 PSTView all revisionsView all revisions

Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
ISBN
9780262039246
Subject Area
Computers
Publication Name
Reinforcement Learning, Second Edition : an Introduction
Publisher
MIT Press
Item Length
11.2 in
Subject
Programming / Algorithms, Intelligence (Ai) & Semantics, Neural Networks
Publication Year
2018
Series
Adaptive Computation and Machine Learning Ser.
Type
Textbook
Format
Hardcover
Language
English
Item Height
1.5 in
Author
Richard S. Sutton, Andrew G. Barto
Item Weight
41.6 Oz
Item Width
7.3 in
Number of Pages
552 Pages

About this product

Product Identifiers

Publisher
MIT Press
ISBN-10
0262039249
ISBN-13
9780262039246
eBay Product ID (ePID)
12038265595

Product Key Features

Number of Pages
552 Pages
Language
English
Publication Name
Reinforcement Learning, Second Edition : an Introduction
Subject
Programming / Algorithms, Intelligence (Ai) & Semantics, Neural Networks
Publication Year
2018
Type
Textbook
Subject Area
Computers
Author
Richard S. Sutton, Andrew G. Barto
Series
Adaptive Computation and Machine Learning Ser.
Format
Hardcover

Dimensions

Item Height
1.5 in
Item Weight
41.6 Oz
Item Length
11.2 in
Item Width
7.3 in

Additional Product Features

Edition Number
2
Intended Audience
Trade
LCCN
2018-023826
Dewey Edition
21
Illustrated
Yes
Dewey Decimal
006.3/1
Synopsis
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.
LC Classification Number
Q325.6.R45 2018

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betterbooksusa0

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622 items sold

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    • m***e (17)- Feedback left by buyer.
      Past year
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      There was no way the book was getting damaged in shipping. Book was new as listed, but I am really impressed on how well they wrapped the book to prevent damage.
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      Received item as advertised.
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    • Right on time

      Nicely packaged and arrived right on time.

      Verified purchase: YesCondition: NewSold by: akabeautyproducts