Reinforcement learning: an introduction Richard S. Sutton and Andrew G. Barto.

By: Contributor(s): Material type: TextTextSeries: Adaptive computation and machine learning seriesPublication details: Cambridge, Massachusetts : The MIT Press, [2018]Edition: Second editionDescription: xxii, 526 pages : illustrations (some color) ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780262039246 (hardcover : alk. paper)
Subject(s): DDC classification:
  • 006.31 22
LOC classification:
  • Q325.6 .R45 2018
Summary: "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."-- Provided by publisher.
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Item type Current library Collection Call number Status Date due Barcode
Books Books Tan Tao University General Stacks Reference 006.31 (Browse shelf(Opens below)) Available A-2022-0019
Books Books Tan Tao University General Stacks Reference 006.31 (Browse shelf(Opens below)) Available A-2022-0018

Includes bibliographical references (pages 481-518) and index.

"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."-- Provided by publisher.

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