000 | 03114nam a22005415i 4500 | ||
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001 | 978-3-030-10546-4 | ||
003 | DE-He213 | ||
005 | 20220801213627.0 | ||
007 | cr nn 008mamaa | ||
008 | 190117s2019 sz | s |||| 0|eng d | ||
020 |
_a9783030105464 _9978-3-030-10546-4 |
||
024 | 7 |
_a10.1007/978-3-030-10546-4 _2doi |
|
050 | 4 | _aTK5103.2-.4885 | |
072 | 7 |
_aTJKW _2bicssc |
|
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_aTEC061000 _2bisacsh |
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072 | 7 |
_aTJKW _2thema |
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082 | 0 | 4 |
_a621.384 _223 |
100 | 1 |
_aYu, F. Richard. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _933289 |
|
245 | 1 | 0 |
_aDeep Reinforcement Learning for Wireless Networks _h[electronic resource] / _cby F. Richard Yu, Ying He. |
250 | _a1st ed. 2019. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2019. |
|
300 |
_aVIII, 71 p. 28 illus., 26 illus. in color. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8120 |
|
520 | _aThis 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. . | ||
650 | 0 |
_aWireless communication systems. _93474 |
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650 | 0 |
_aMobile communication systems. _94051 |
|
650 | 0 |
_aArtificial intelligence. _93407 |
|
650 | 0 |
_aTelecommunication. _910437 |
|
650 | 1 | 4 |
_aWireless and Mobile Communication. _933290 |
650 | 2 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aCommunications Engineering, Networks. _931570 |
700 | 1 |
_aHe, Ying. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _933291 |
|
710 | 2 |
_aSpringerLink (Online service) _933292 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783030105457 |
776 | 0 | 8 |
_iPrinted edition: _z9783030105471 |
830 | 0 |
_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8120 _933293 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-10546-4 |
912 | _aZDB-2-ENG | ||
912 | _aZDB-2-SXE | ||
942 | _cEBK | ||
999 |
_c75408 _d75408 |