Deep Reinforcement Learning for Wireless Networks (Record no. 75408)
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fixed length control field | 03114nam a22005415i 4500 |
001 - CONTROL NUMBER | |
control field | 978-3-030-10546-4 |
005 - DATE AND TIME OF LATEST TRANSACTION | |
control field | 20220801213627.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
fixed length control field | 190117s2019 sz | s |||| 0|eng d |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
ISBN | 9783030105464 |
-- | 978-3-030-10546-4 |
082 04 - CLASSIFICATION NUMBER | |
Call Number | 621.384 |
100 1# - AUTHOR NAME | |
Author | Yu, F. Richard. |
245 10 - TITLE STATEMENT | |
Title | Deep Reinforcement Learning for Wireless Networks |
250 ## - EDITION STATEMENT | |
Edition statement | 1st ed. 2019. |
300 ## - PHYSICAL DESCRIPTION | |
Number of Pages | VIII, 71 p. 28 illus., 26 illus. in color. |
490 1# - SERIES STATEMENT | |
Series statement | SpringerBriefs in Electrical and Computer Engineering, |
520 ## - SUMMARY, ETC. | |
Summary, etc | This Springerbrief presents a deep reinforcement learning approach to wireless systems to improve system performance. Particularly, deep reinforcement learning approach is used in cache-enabled opportunistic interference alignment wireless networks and mobile social networks. Simulation results with different network parameters are presented to show the effectiveness of the proposed scheme. There is a phenomenal burst of research activities in artificial intelligence, deep reinforcement learning and wireless systems. Deep reinforcement learning has been successfully used to solve many practical problems. For example, Google DeepMind adopts this method on several artificial intelligent projects with big data (e.g., AlphaGo), and gets quite good results.. Graduate students in electrical and computer engineering, as well as computer science will find this brief useful as a study guide. Researchers, engineers, computer scientists, programmers, and policy makers will also find this brief to be a useful tool. . |
700 1# - AUTHOR 2 | |
Author 2 | He, Ying. |
856 40 - ELECTRONIC LOCATION AND ACCESS | |
Uniform Resource Identifier | https://doi.org/10.1007/978-3-030-10546-4 |
942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
Koha item type | eBooks |
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-- | Springer International Publishing : |
-- | Imprint: Springer, |
-- | 2019. |
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-- | computer |
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-- | online resource |
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347 ## - | |
-- | text file |
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-- | rda |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Wireless communication systems. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Mobile communication systems. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial intelligence. |
650 #0 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Telecommunication. |
650 14 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Wireless and Mobile Communication. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Artificial Intelligence. |
650 24 - SUBJECT ADDED ENTRY--SUBJECT 1 | |
-- | Communications Engineering, Networks. |
830 #0 - SERIES ADDED ENTRY--UNIFORM TITLE | |
-- | 2191-8120 |
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-- | ZDB-2-ENG |
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-- | ZDB-2-SXE |
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