000 | 03290nam a22005535i 4500 | ||
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001 | 978-3-031-01561-8 | ||
003 | DE-He213 | ||
005 | 20240730165129.0 | ||
007 | cr nn 008mamaa | ||
008 | 220601s2013 sz | s |||| 0|eng d | ||
020 |
_a9783031015618 _9978-3-031-01561-8 |
||
024 | 7 |
_a10.1007/978-3-031-01561-8 _2doi |
|
050 | 4 | _aQ334-342 | |
050 | 4 | _aTA347.A78 | |
072 | 7 |
_aUYQ _2bicssc |
|
072 | 7 |
_aCOM004000 _2bisacsh |
|
072 | 7 |
_aUYQ _2thema |
|
082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aGebser, Martin. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _987564 |
|
245 | 1 | 0 |
_aAnswer Set Solving in Practice _h[electronic resource] / _cby Martin Gebser, Roland Kaminski, Benjamin Kaufmann, Torsten Schaub. |
250 | _a1st ed. 2013. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2013. |
|
300 |
_aXXV, 212 p. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aSynthesis Lectures on Artificial Intelligence and Machine Learning, _x1939-4616 |
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505 | 0 | _aList of Figures -- List of Tables -- Motivation -- Introduction -- Basic modeling -- Grounding -- Characterizations -- Solving -- Systems -- Advanced modeling -- Conclusions. | |
520 | _aAnswer Set Programming (ASP) is a declarative problem solving approach, initially tailored to modeling problems in the area of Knowledge Representation and Reasoning (KRR). More recently, its attractive combination of a rich yet simple modeling language with high-performance solving capacities has sparked interest in many other areas even beyond KRR. This book presents a practical introduction to ASP, aiming at using ASP languages and systems for solving application problems. Starting from the essential formal foundations, it introduces ASP's solving technology, modeling language and methodology, while illustrating the overall solving process by practical examples. Table of Contents: List of Figures / List of Tables / Motivation / Introduction / Basic modeling / Grounding / Characterizations / Solving / Systems / Advanced modeling / Conclusions. | ||
650 | 0 |
_aArtificial intelligence. _93407 |
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650 | 0 |
_aMachine learning. _91831 |
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650 | 0 |
_aNeural networks (Computer science) . _987566 |
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650 | 1 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aMachine Learning. _91831 |
650 | 2 | 4 |
_aMathematical Models of Cognitive Processes and Neural Networks. _932913 |
700 | 1 |
_aKaminski, Roland. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _987568 |
|
700 | 1 |
_aKaufmann, Benjamin. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _987570 |
|
700 | 1 |
_aSchaub, Torsten. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _987572 |
|
710 | 2 |
_aSpringerLink (Online service) _987575 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031004339 |
776 | 0 | 8 |
_iPrinted edition: _z9783031026898 |
830 | 0 |
_aSynthesis Lectures on Artificial Intelligence and Machine Learning, _x1939-4616 _987576 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-01561-8 |
912 | _aZDB-2-SXSC | ||
942 | _cEBK | ||
999 |
_c86117 _d86117 |