| 000 | 01818naaaa2200301uu 4500 | ||
|---|---|---|---|
| 001 | https://directory.doabooks.org/handle/20.500.12854/64908 | ||
| 005 | 20220220070920.0 | ||
| 020 | _a557 | ||
| 020 | _a9789533073699 | ||
| 020 | _a9789535155034 | ||
| 024 | 7 |
_a10.5772/557 _cdoi |
|
| 041 | 0 | _aEnglish | |
| 042 | _adc | ||
| 072 | 7 |
_aUYQ _2bicssc |
|
| 100 | 1 |
_aMellouk, Abdelhamid _4edt |
|
| 700 | 1 |
_aMellouk, Abdelhamid _4oth |
|
| 245 | 1 | 0 | _aAdvances in Reinforcement Learning |
| 260 |
_bIntechOpen _c2011 |
||
| 300 | _a1 electronic resource (484 p.) | ||
| 506 | 0 |
_aOpen Access _2star _fUnrestricted online access |
|
| 520 | _aReinforcement Learning (RL) is a very dynamic area in terms of theory and application. This book brings together many different aspects of the current research on several fields associated to RL which has been growing rapidly, producing a wide variety of learning algorithms for different applications. Based on 24 Chapters, it covers a very broad variety of topics in RL and their application in autonomous systems. A set of chapters in this book provide a general overview of RL while other chapters focus mostly on the applications of RL paradigms: Game Theory, Multi-Agent Theory, Robotic, Networking Technologies, Vehicular Navigation, Medicine and Industrial Logistic. | ||
| 540 |
_aCreative Commons _fhttps://creativecommons.org/licenses/by-nc-sa/3.0/ _2cc _4https://creativecommons.org/licenses/by-nc-sa/3.0/ |
||
| 546 | _aEnglish | ||
| 650 | 7 |
_aArtificial intelligence _2bicssc |
|
| 653 | _aMachine learning | ||
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://mts.intechopen.com/storage/books/24/authors_book/authors_book.pdf _70 _zDOAB: download the publication |
| 856 | 4 | 0 |
_awww.oapen.org _uhttps://directory.doabooks.org/handle/20.500.12854/64908 _70 _zDOAB: description of the publication |
| 999 |
_c72436 _d72436 |
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