Reinforcement learning : an introduction / Richard S. Sutton and Andrew G. Barto.
By: Sutton, Richard S [author.].
Contributor(s): Barto, Andrew G [author.].
Series: Adaptive computation and machine learning series.Publisher: Cambridge, Massachusetts : The MIT Press, ©2018Edition: Second edition.Description: 526 pages ; illustrations (some color) ; 24 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9780262039246 (hardcover : alk. paper).Subject(s): Reinforcement learningGenre/Form: Print books.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."--Current location | Call number | Status | Date due | Barcode | Item holds |
---|---|---|---|---|---|
On Shelf | Q325.6 .R45 2018 (Browse shelf) | Available | AU00000000014505 |
Browsing Alfaisal University Shelves , Shelving location: On Shelf Close shelf browser
Q325.5 .W38 2016 Machine learning refined : foundations, algorithms, and applications / | Q325.5 .Z44 2018 Feature engineering for machine learning : principles and techniques for data scientists / | Q325.6 .G73 2020 Foundations of deep reinforcement learning : theory and practice in Python / | Q325.6 .R45 2018 Reinforcement learning : an introduction / | Q325.6 .S39 2014 Multi-agent machine learning : a reinforcement approach / | Q325.7 .C43 2018 Introduction to deep learning / | Q325.73 .P75 2023 Understanding deep learning / |
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."--