Reinforcement learning : an introduction / Richard S. Sutton and Andrew G. Barto.
Material type:![Text](/opac-tmpl/lib/famfamfam/BK.png)
- 9780262039246 (hardcover : alk. paper)
- 006.31 SUT
Item type | Current library | Home library | Collection | Call number | Status | Date due | Barcode | |
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Dept. of Computer Science Reference | Dept. of Computer Science | 006.31 SUT (Browse shelf(Opens below)) | Available | DCS4870 | |||
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Dept. of Futures Studies Reference | Dept. of Futures Studies | Reference | R 006.31 SUT;1 (Browse shelf(Opens below)) | Available | DFS4500 | ||
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Dept. of Futures Studies Processing Center | Dept. of Futures Studies | 006.31 SUT (Browse shelf(Opens below)) | Available | DFS4357 |
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."--
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