| 000 | 01785nam a2200397 i 4500 | ||
|---|---|---|---|
| 001 | EBC5434975 | ||
| 003 | MiAaPQ | ||
| 007 | cr cnu|||||||| | ||
| 008 | 180706s2018 enk ob 001 0 eng d | ||
| 020 | _z9781788834247 | ||
| 020 | _a9781788839303 (e-book) | ||
| 035 | _a(MiAaPQ)EBC5434975 | ||
| 035 | _a(Au-PeEL)EBL5434975 | ||
| 035 | _a(CaPaEBR)ebr11584858 | ||
| 035 | _a(OCoLC)1042318736 | ||
| 040 |
_aMiAaPQ _beng _erda _epn _cMiAaPQ _dMiAaPQ |
||
| 050 | 4 |
_aQ325.6 _b.L373 2018 |
|
| 082 | 0 |
_a006.31 _223 |
|
| 100 | 1 |
_aLapan, Maxim, _eauthor. |
|
| 245 | 1 | 0 |
_aDeep reinforcement learning hands-on : _bapply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more / _cMaxim Lapan. |
| 264 | 1 |
_aBirmingham, England : _bPackt Publishing, _c2018. |
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| 300 | _a1 online resource (547 pages) | ||
| 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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| 504 | _aIncludes bibliographical references and index. | ||
| 588 | _aDescription based on print version record. | ||
| 590 | _aElectronic reproduction. Ann Arbor, MI : ProQuest, 2018. Available via World Wide Web. Access may be limited to ProQuest affiliated libraries. | ||
| 650 | 0 | _aReinforcement learning. | |
| 655 | 4 | _aElectronic books. | |
| 776 | 0 | 8 |
_iPrint version: _aLapan, Maxim. _tDeep reinforcement learning hands-on : apply modern RL methods, with deep Q-networks, value iteration, policy gradients, TRPO, AlphaGo Zero and more. _dBirmingham, England : Packt Publishing, c2018 _h547 pages _z9781788834247 |
| 797 | 2 | _aProQuest (Firm) | |
| 856 | 4 | 0 |
_uhttps://ebookcentral.proquest.com/lib/kliuc-ebooks/detail.action?docID=5434975 _zClick to View |
| 942 |
_2lcc _cEBK |
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| 999 |
_c305681 _d305681 |
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