"Neurons and Symbols", the successor to the authors' work "An Introduction to Neural Computing", presents in a unified explanatory style the emerging points of a fierce contemporary debate on the effect that neural models are likely to have on more classic symbolic models of cognition. The controversy is multi-disciplinary - it involves scientists and technologists who are trying to build machines with cognitive properties, computer theoreticians interested in artificial intelligence, cognitive scientists and psychologists who are trying to find appropriate representations for cognition, philosophers who would like to explain concepts of the mind and linguists who are concerned with the role of language in cognition. The non-mathematical approach of this book lays bare the arguments that are put forward by those who, on the one hand, believe that the way to understand cognition is by knowing what the neural networks of the brain are doing, and on the other, those who believe that a program-like symbolic representation is the way to explain things. Is there a compromise between the two? The authors believe that there is and present the results of their own research in the area.
Being interdisciplinary, one of the aims of the book is to start from first principles in everything, providing the reader with sufficient background in neural systems, artificial intelligence, cognitive science, automata theory and computational theory.
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Sprache
Verlagsort
Zielgruppe
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Maße
Höhe: 234 mm
Breite: 156 mm
ISBN-13
978-0-412-46090-6 (9780412460906)
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Schweitzer Klassifikation
The stuff that mind is made of - of string, sealing wax, battles, neurons and symbols; artificial neural nets - bare bones and some cognitive properties; artificial intelligence - of symbols and algorithms; cognitive science - a symbolic enterprise; neural automata - the ghost of any machine; the great debate - of symbols and sub-symbols; the illusion in the battle - a continuum between neurons and consciousness?; language and neurons - the medium and the message; seeing and thinking - does the mind have an eye?; the architectures of cognition - reverse-engineering in the mind; a proper future for cognitive models - of truce, a better understanding and better machines.
