000 | 03269nam a22005175i 4500 | ||
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001 | 978-3-031-01547-2 | ||
003 | DE-He213 | ||
005 | 20240730163426.0 | ||
007 | cr nn 008mamaa | ||
008 | 220601s2008 sz | s |||| 0|eng d | ||
020 |
_a9783031015472 _9978-3-031-01547-2 |
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024 | 7 |
_a10.1007/978-3-031-01547-2 _2doi |
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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 |
_aThielscher, Michael. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _978435 |
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245 | 1 | 0 |
_aAction Programming Languages _h[electronic resource] / _cby Michael Thielscher. |
250 | _a1st ed. 2008. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2008. |
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300 |
_aVIII, 91 p. _bonline resource. |
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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 |
_aSynthesis Lectures on Artificial Intelligence and Machine Learning, _x1939-4616 |
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505 | 0 | _aIntroduction -- Mathematical Preliminaries -- Procedural Action Programs -- Action Programs and Planning -- Declarative Action Programs -- Reactive Action Programs -- Suggested Further Reading. | |
520 | _aArtificial systems that think and behave intelligently are one of the most exciting and challenging goals of Artificial Intelligence. Action Programming is the art and science of devising high-level control strategies for autonomous systems which employ a mental model of their environment and which reason about their actions as a means to achieve their goals. Applications of this programming paradigm include autonomous software agents, mobile robots with high-level reasoning capabilities, and General Game Playing. These lecture notes give an in-depth introduction to the current state-of-the-art in action programming. The main topics are knowledge representation for actions, procedural action programming, planning, agent logic programs, and reactive, behavior-based agents. The only prerequisite for understanding the material in these lecture notes is some general programming experience and basic knowledge of classical first-order logic. Table of Contents: Introduction / Mathematical Preliminaries / Procedural Action Programs / Action Programs and Planning / Declarative Action Programs / Reactive Action Programs / Suggested Further Reading. | ||
650 | 0 |
_aArtificial intelligence. _93407 |
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650 | 0 |
_aMachine learning. _91831 |
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650 | 0 |
_aNeural networks (Computer science) . _978436 |
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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 |
710 | 2 |
_aSpringerLink (Online service) _978437 |
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773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031004193 |
776 | 0 | 8 |
_iPrinted edition: _z9783031026751 |
830 | 0 |
_aSynthesis Lectures on Artificial Intelligence and Machine Learning, _x1939-4616 _978438 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-01547-2 |
912 | _aZDB-2-SXSC | ||
942 | _cEBK | ||
999 |
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