Reinforcement learning [2nd ed.] (Record no. 564922)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02306 a2200241 4500 |
| 003 - CONTROL NUMBER IDENTIFIER | |
| control field | OSt |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9780262039246 |
| 040 ## - CATALOGING SOURCE | |
| Transcribing agency | IIT Kanpur |
| 041 ## - LANGUAGE CODE | |
| Language code of text/sound track or separate title | eng |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 006.31 |
| Item number | Su87r2 |
| 100 ## - MAIN ENTRY--AUTHOR NAME | |
| Personal name | Sutton, Richard S. |
| 245 ## - TITLE STATEMENT | |
| Title | Reinforcement learning [2nd ed.] |
| Remainder of title | an introduction |
| Statement of responsibility, etc | Richard S. Sutton and Andrew G. Barto |
| 250 ## - EDITION STATEMENT | |
| Edition statement | 2nd ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher | MIT Press |
| Year of publication | 2018 |
| Place of publication | Cambridge |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xxii, 526p |
| 440 ## - SERIES STATEMENT/ADDED ENTRY--TITLE | |
| Title | Adaptive computation and machine learning |
| 490 ## - SERIES STATEMENT | |
| Series statement | / edited by Francis Bach |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence.<br/><br/>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. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics.<br/><br/>Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Reinforcement learning |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Artificial intelligence |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Barto, Andrew G. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Withdrawn status | Lost status | Damaged status | Not for loan | Collection code | Home library | Current library | Date acquired | Source of acquisition | Cost, normal purchase price | Full call number | Accession Number | Cost, replacement price | Koha item type |
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| General Stacks | PK Kelkar Library, IIT Kanpur | PK Kelkar Library, IIT Kanpur | 08/11/2021 | 2 | 4819.20 | 006.31 Su87r2 | A185373 | 4819.20 | Books |