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001			297350
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008			150903s2009 gw | o |||| 0|eng d
020			_a9783540732464 _99783540732464
024	7		_a10.1007/9783540732464 _2doi
035			_avtls000350521
039		9	_a201509030459 _bVLOAD _c201405050352 _dVLOAD _y201402171059 _zstaff
040			_aMX-SnUAN _bspa _cMX-SnUAN _erda
050		4	_aQ334-342
100	1		_ad’Avila Garcez, Artur S. _eautor _9333061
245	1	0	_aNeural-Symbolic Cognitive Reasoning / _cby Artur S. d’Avila Garcez, Luís C. Lamb, Dov M. Gabbay.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2009.
300			_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		_aCognitive Technologies, _x1611-2482
500			_aSpringer eBooks
505	0		_aLogic and Knowledge Representation -- Artificial Neural Networks -- Neural-Symbolic Learning Systems -- Connectionist Modal Logic -- Connectionist Temporal Reasoning -- Connectionist Intuitionistic Reasoning -- Applications of Connectionist Nonclassical Reasoning -- Fibring Neural Networks -- Relational Learning in Neural Networks -- Argumentation Frameworks as Neural Networks -- Reasoning about Probabilities in Neural Networks -- Conclusions.
520			_aHumans are often extraordinary at performing practical reasoning. There are cases where the human computer, slow as it is, is faster than any artificial intelligence system. Are we faster because of the way we perceive knowledge as opposed to the way we represent it? The authors address this question by presenting neural network models that integrate the two most fundamental phenomena of cognition: our ability to learn from experience, and our ability to reason from what has been learned. This book is the first to offer a self-contained presentation of neural network models for a number of computer science logics, including modal, temporal, and epistemic logics. By using a graphical presentation, it explains neural networks through a sound neural-symbolic integration methodology, and it focuses on the benefits of integrating effective robust learning with expressive reasoning capabilities. The book will be invaluable reading for academic researchers, graduate students, and senior undergraduates in computer science, artificial intelligence, machine learning, cognitive science and engineering. It will also be of interest to computational logicians, and professional specialists on applications of cognitive, hybrid and artificial intelligence systems.
590			_aPara consulta fuera de la UANL se requiere clave de acceso remoto.
700	1		_aLamb, Luís C. _eautor _9333062
700	1		_aGabbay, Dov M. _eautor _9300815
710	2		_aSpringerLink (Servicio en línea) _9299170
776	0	8	_iEdición impresa: _z9783540732457
856	4	0	_uhttp://remoto.dgb.uanl.mx/login?url=http://dx.doi.org/10.1007/978-3-540-73246-4 _zConectar a Springer E-Books (Para consulta externa se requiere previa autentificación en Biblioteca Digital UANL)
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