ENGLISH

Neural-Symbolic Cognitive Reasoning

By Dr. Artur S. d’Avila Garcez , Dr. Luís C. Lamb , Prof. Dov M. Gabbay (auth.)

Book information

Publisher
Springer-Verlag Berlin Heidelberg
Year
2009
ISBN
9783540732457, 9783540732464, 3540732454
DOI
10.1007/978-3-540-73246-4
LCC
QA76.87 .D39 2009
Open Library ID
OL23207352M
Language
english
Format
PDF
Filesize
1 MB (1510303 bytes)
Series
Cognitive Technologies
Edition
1
Pages
198\200
Topic
Medicine Neurology
Scanned
yes
Time added
2011-04-20 14:05:05
Artificial Intelligence (incl. Robotics); Computat

Description

Humans 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.

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