000 | 03303nam a22006135i 4500 | ||
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001 | 978-3-031-21003-7 | ||
003 | DE-He213 | ||
005 | 20240730163859.0 | ||
007 | cr nn 008mamaa | ||
008 | 230220s2023 sz | s |||| 0|eng d | ||
020 |
_a9783031210037 _9978-3-031-21003-7 |
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024 | 7 |
_a10.1007/978-3-031-21003-7 _2doi |
|
050 | 4 | _aQ334-342 | |
050 | 4 | _aTA347.A78 | |
072 | 7 |
_aUYQ _2bicssc |
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072 | 7 |
_aCOM004000 _2bisacsh |
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_aUYQ _2thema |
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_a006.3 _223 |
100 | 1 |
_aBelle, Vaishak. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _981007 |
|
245 | 1 | 0 |
_aToward Robots That Reason: Logic, Probability & Causal Laws _h[electronic resource] / _cby Vaishak Belle. |
250 | _a1st ed. 2023. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2023. |
|
300 |
_aXIII, 190 p. 27 illus., 14 illus. in color. _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 |
|
505 | 0 | _aPreface -- Acknowledgments -- Introduction -- Representation Matters -- From Predicate Calculus to the Situation Calculus -- Knowledge -- Probabilistic Beliefs -- Continuous Distributions -- Localization -- Regression & Progression -- Programs -- A Modal Reconstruction -- Conclusions. | |
520 | _aThis book discusses the two fundamental elements that underline the science and design of artificial intelligence (AI) systems: the learning and acquisition of knowledge from observational data, and the reasoning of that knowledge together with whatever information is available about the application at hand. It then presents a mathematical treatment of the core issues that arise when unifying first-order logic and probability, especially in the presence of dynamics, including physical actions, sensing actions and their effects. A model for expressing causal laws describing dynamics is also considered, along with computational ideas for reasoning with such laws over probabilistic logical knowledge. . | ||
650 | 0 |
_aArtificial intelligence. _93407 |
|
650 | 0 |
_aRobotics. _92393 |
|
650 | 0 |
_aComputer science _xMathematics. _93866 |
|
650 | 0 |
_aMathematical statistics. _99597 |
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650 | 0 |
_aLogic design. _93686 |
|
650 | 0 |
_aApplication software. _981008 |
|
650 | 0 |
_aData mining. _93907 |
|
650 | 1 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aRobotics. _92393 |
650 | 2 | 4 |
_aProbability and Statistics in Computer Science. _931857 |
650 | 2 | 4 |
_aLogic Design. _93686 |
650 | 2 | 4 |
_aComputer and Information Systems Applications. _981009 |
650 | 2 | 4 |
_aData Mining and Knowledge Discovery. _981010 |
710 | 2 |
_aSpringerLink (Online service) _981011 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031210020 |
776 | 0 | 8 |
_iPrinted edition: _z9783031210044 |
776 | 0 | 8 |
_iPrinted edition: _z9783031210051 |
830 | 0 |
_aSynthesis Lectures on Artificial Intelligence and Machine Learning, _x1939-4616 _981012 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-21003-7 |
912 | _aZDB-2-SXSC | ||
942 | _cEBK | ||
999 |
_c85086 _d85086 |