MTU Cork Library Catalogue

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Paradigms of artificial intelligence : a methodological and computational analysis / by Achim Gnther Hoffmann.

By: Hoffmann, Achim Gnther, 1962-.
Material type: materialTypeLabelBookPublisher: New York : Springer Verlag, 1998Description: xiii, 332 p. ; 24 cm. + pbk.ISBN: 9813083972.Subject(s): Artificial intelligence -- Methodology | Paradigm (Theory of knowledge) | CognitionDDC classification: 006.3
Contents:
Introduction -- Part I: The symbolic paradigm -- Foundations of the symbolic paradigm -- Knowledge representation and reasoning -- Expert systems -- Symbolic learning -- Summary of the symbolic paradigm -- Part II: The connectionist paradigm -- Foundations of the connectionist paradigm -- Connectionist computing models -- Integrating symbols into connectionist models -- Summary of the connectionist paradigm -- Part III: Methodological analysis of the two paradigms -- Formal foundations -- Levels of description -- The notion of 'symbols' -- Computational limitations of connectionist architectures -- Methodological discussion -- Non-factual knowledge -- Conclusions.
Holdings
Item type Current library Call number Copy number Status Date due Barcode Item holds
General Lending MTU Bishopstown Library Lending 006.3 (Browse shelf(Opens below)) 1 Available 00086082
General Lending MTU Bishopstown Library Lending 006.3 (Browse shelf(Opens below)) 1 Available 00086083
Total holds: 0

Enhanced descriptions from Syndetics:

This book presents a new methodological analysis of two competing research paradigms of artificial intelligence and cognitive science-the symbolic versus the connectionist paradigms. Providing an accessible introduction to the fundamentals of both paradigms, the book derives new objectives for future research that will help to integrate aspects of both areas to obtain more powerful AI techniques and to promote a deeper understanding of cognition.

Bibliography: (pages 303-322) and indexes.

Introduction -- Part I: The symbolic paradigm -- Foundations of the symbolic paradigm -- Knowledge representation and reasoning -- Expert systems -- Symbolic learning -- Summary of the symbolic paradigm -- Part II: The connectionist paradigm -- Foundations of the connectionist paradigm -- Connectionist computing models -- Integrating symbols into connectionist models -- Summary of the connectionist paradigm -- Part III: Methodological analysis of the two paradigms -- Formal foundations -- Levels of description -- The notion of 'symbols' -- Computational limitations of connectionist architectures -- Methodological discussion -- Non-factual knowledge -- Conclusions.

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