000			03514nam a22004215i 4500
001			978-0-387-76872-4
003			DE-He213
005			20250710084025.0
007			cr nn 008mamaa
008			110402s2009 xxu| s |||| 0|eng d
020			_a9780387768724 _a99780387768724
024	7		_a10.1007/978-0-387-76872-4 _2doi
100	1		_aGoertzel, Ben. _eauthor.
245	1	0	_aProbabilistic Logic Networks _h[recurso electrónico] : _bA Comprehensive Framework for Uncertain Inference / _cby Ben Goertzel, Matthew Iklé, Izabela Freire Goertzel, Ari Heljakka.
264		1	_aBoston, MA : _bSpringer US, _c2009.
300			_aVIII, 336p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_arecurso en línea _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aKnowledge Representation -- Experiential Semantics -- Indefinite Truth Values -- First-Order Extensional Inference: Rules and Strength Formulas -- First-Order Extensional Inference with Indefinite Truth Values -- First-Order Extensional Inference with Distributional Truth Values -- Error Magnification in Inference Formulas -- Large-Scale Inference Strategies -- Higher-Order Extensional Inference -- Handling Crisp and Fuzzy Quantifiers with Indefinite Truth Values -- Intensional Inference -- Aspects of Inference Control -- Temporal and Causal Inference.
520			_aThis book describes Probabilistic Logic Networks (PLN), a novel conceptual, mathematical and computational approach to uncertain inference. Going beyond prior probabilistic approaches to uncertain inference, PLN encompasses such ideas as induction, abduction, analogy, fuzziness and speculation, and reasoning about time and causality. The book provides an overview of PLN in the context of other approaches to uncertain inference. Topics addressed in the text include: the basic formalism of PLN knowledge representation the conceptual interpretation of the terms used in PLN an indefinite probability approach to quantifying uncertainty, providing a general method for calculating the "weight-of-evidence" underlying the conclusions of uncertain inference specific PLN inference rules and the corresponding truth-value formulas used to determine the strength of the conclusion of an inference rule from the strengths of the premises large-scale inference strategies inference using variables indefinite probabilities involving quantifiers inheritance based on properties or patterns the Novamente Cognition Engine, an application of PLN temporal and causal logic in PLN Researchers and graduate students in artificial intelligence, computer science, mathematics and cognitive sciences will find this novel perspective on uncertain inference a thought-provoking integration of ideas from a variety of other lines of inquiry.
650		0	_aCOMPUTER SCIENCE.
650		0	_aARTIFICIAL INTELLIGENCE.
650	1	4	_aCOMPUTER SCIENCE.
650	2	4	_aARTIFICIAL INTELLIGENCE (INCL. ROBOTICS).
650	2	4	_aMATH APPLICATIONS IN COMPUTER SCIENCE.
700	1		_aIklé, Matthew. _eauthor.
700	1		_aGoertzel, Izabela Freire. _eauthor.
700	1		_aHeljakka, Ari. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387768717
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-76872-4 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SCS
942			_2ddc _cER
999			_c58842 _d58842