| 000 -LEADER |
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| fixed length control field |
a |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
231101b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781316511961 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
006.3 |
| Item number |
MEY |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Meyn, S. P. |
| 245 ## - TITLE STATEMENT |
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| Title |
Control systems and reinforcement learning |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc |
Cambridge University Press, |
| Date of publication, distribution, etc |
2022 |
| Place of publication, distribution, etc |
Cambridge : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xv, 435 p. ; |
| Other physical details |
ill., |
| Dimensions |
27 cm. |
| 365 ## - TRADE PRICE |
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| Price amount |
49.99 |
| Price type code |
GBP |
| Unit of pricing |
107.60 |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
A high school student can create deep Q-learning code to control her robot, without any understanding of the meaning of "deep" or "Q", or why the code sometimes fails. This book is designed to explain the science behind reinforcement learning and optimal control in a way that is accessible to students with a background in calculus and matrix algebra. A unique focus is algorithm design to obtain the fastest possible speed of convergence for learning algorithms, along with insight into why reinforcement learning sometimes fails. Advanced stochastic process theory is avoided at the start by substituting random exploration with more intuitive deterministic probing for learning. Once these ideas are understood, it is not difficult to master techniques rooted in stochastic control. These topics are covered in the second part of the book, starting with Markov chain theory and ending with a fresh look at actor-critic methods for reinforcement learning. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Control theory |
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| Topical term or geographic name as entry element |
Mathematical optimization |
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| Topical term or geographic name as entry element |
Computer vision |
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| Topical term or geographic name as entry element |
Pattern recognition |
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| Topical term or geographic name as entry element |
Stochastic Processes |
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| Topical term or geographic name as entry element |
Econometrics |
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| Topical term or geographic name as entry element |
Cost function |
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| Topical term or geographic name as entry element |
Contro theory |
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| Topical term or geographic name as entry element |
Approximation |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
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| Item type |
Books |