Reinforcement learning : an introduction /
"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, Richar...
| Main Authors: | , |
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| 格式: | 图书 |
| 语言: | English |
| 出版: |
Cambridge, Massachusetts :
The MIT Press,
c2018
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| 版: | Second edition. |
| 丛编: | Adaptive computation and machine learning series
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| 主题: | |
| Classic Catalogue: | View this record in Classic Catalogue |
| 总结: | "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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| 实物描述: | xxii, 526 pages : illustrations (some color) ; 23 cm. |
| 参考书目: | Includes bibliographical references (pages [481]-518) and index. |
| ISBN: | 9780262039246 (hardcover : alk. paper) |