000 02924nam a22003735i 4500
001 278015
003 MX-SnUAN
005 20170705134200.0
007 cr nn 008mamaa
008 150903s2006 xxu| o |||| 0|eng d
020 _a9780387302621
_99780387302621
024 7 _a10.1007/038730262-X
_2doi
035 _avtls000330817
039 9 _a201509030725
_bVLOAD
_c201404120535
_dVLOAD
_c201404090316
_dVLOAD
_c201401311352
_dstaff
_y201401301155
_zstaff
040 _aMX-SnUAN
_bspa
_cMX-SnUAN
_erda
050 4 _aQ334-342
100 1 _aLawry, Jonathan.
_eautor
_9301309
245 1 0 _aModelling and Reasoning with Vague Concepts /
_cby Jonathan Lawry.
264 1 _aBoston, MA :
_bSpringer US,
_c2006.
300 _axxv, 246 páginas,
_brecurso en línea.
336 _atexto
_btxt
_2rdacontent
337 _acomputadora
_bc
_2rdamedia
338 _arecurso en línea
_bcr
_2rdacarrier
347 _aarchivo de texto
_bPDF
_2rda
490 0 _aStudies in Computational Intelligence,
_x1860-949X ;
_v12
500 _aSpringer eBooks
505 0 _aVague Concepts and Fuzzy Sets -- Label Semantics -- Multi-Dimensional and Multi-Instance Label Semantics -- Information from Vague Concepts -- Learning Linguistic Models from Data -- Fusing Knowledge and Data -- Non-Additive Appropriateness Measures.
520 _aVagueness is central to the flexibility and robustness of natural language descriptions. Vague concepts are robust to the imprecision of our perceptions, while still allowing us to convey useful, and sometimes vital, information. The study of vagueness in Artificial Intelligence (AI) is therefore motivated by the desire to incorporate this robustness and flexibility into intelligent computer systems. Such a goal, however, requires a formal model of vague concepts that will allow us to quantify and manipulate the uncertainty resulting from their use as a means of passing information between autonomous agents. This volume outlines a formal representation framework for modelling and reasoning with vague concepts in Artificial Intelligence. The new calculus has many applications, especially in automated reasoning, learning, data analysis and information fusion. This book gives a rigorous introduction to label semantics theory, illustrated with many examples, and suggests clear operational interpretations of the proposed measures. It also provides a detailed description of how the theory can be applied in data analysis and information fusion based on a range of benchmark problems.
590 _aPara consulta fuera de la UANL se requiere clave de acceso remoto.
710 2 _aSpringerLink (Servicio en línea)
_9299170
776 0 8 _iEdición impresa:
_z9780387290560
856 4 0 _uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/0-387-30262-X
_zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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999 _c278015
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