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

By: Contributor(s): Material type: TextTextSeries: Adaptive computation and machine learning seriesPublisher: Cambridge, Massachusetts : The MIT Press, [2018]Edition: 2nd edDescription: xxii, 526 pages : illustrations (some color) ; 24 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9780262039246
Subject(s): DDC classification:
  • 006.31 23
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.
Item type: Books
Holdings
Item type Current library Shelving location Call number Copy number Status Date due Barcode Item holds
Books IUT Library General Stacks 006.31 SUR 01 Available 0000045466
Books IUT Library General Stacks 006.31 SUR 02 Available 0000045467
Books IUT Library General Stacks 006.31 SUR 03 Available 0000045468
Books IUT Library General Stacks 006.31 SUR 04 Available 0000045469
Books IUT Library General Stacks 006.31 SUR 05 Available 0000045470
Books IUT Library General Stacks 006.31 SUR 06 Checked out 04/18/2026 0000045471
Books IUT Library General Stacks 006.31 SUR 07 Checked out 04/18/2026 0000045472
Books IUT Library General Stacks 006.31 SUR 08 Checked out 04/28/2026 0000045473
Books IUT Library General Stacks 006.31 SUR 09 Checked out 03/28/2026 0000045474
Books IUT Library General Stacks 006.31 SUR 10 Checked out 04/16/2026 0000045475
Total holds: 0

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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