Reinforcement learning : an introduction Richard S. Sutton and Andrew G. Barto.
Material type:
TextSeries: Adaptive computation and machine learning seriesPublisher: Cambridge, Massachusetts : The MIT Press, 2020Edition: Second editionDescription: xxii, 526 pages : illustrations (some color) ; 24 cmContent type: text Media type: unmediated Carrier type: volumeISBN: 9780262039246 (hardcover : alk. paper)Subject(s): Reinforcement learning | E-BOOKBANK.SEECSTEXTBOOKDDC classification: 006.31 LOC classification: Q325.6 | .R45 2018Online resources: Click here to access online 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 | Current location | Home library | Call number | Status | Date due | Barcode | Item holds |
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Central Library (CL) | Central Library (CL) | 280 SCB (Browse shelf) | Available | SCB-1578 | ||
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Central Library (CL) | Central Library (CL) | 006.31 SUT (Browse shelf) | Available | CL-1578 |
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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