Overview

This text focuses on a currently emerging body of research. With the re-emergence of neural networks in the 1980s with their emphasis on overcoming some of the limitations of symbolic AI, there is clearly a need to support some form of high-level symbolic processing in connectionist networks. As argued by many researchers, on both the symbolic AI and connectionist sides, many cognitive tasks, e.g. language understanding and common sense reasoning, seem to require high-level symbolic capabilities. How these capabilities are realized in connectionist networks is a difficult question and it constitutes the focus of this book. It addresses the underlying architectural aspects of the integration of neural and symbolic processes. In order to provide a basis for a deeper understanding of existing divergent approaches and provide insight for further developments in this field, this book presents: (1) an examination of specific architectures (grouped together according to their approaches), their strengths and weaknesses, why they work, and what they predict, and (2) a critique/comparison of these approaches. This text should be of interest to researchers, graduate students, and interested laymen, in areas such as cognitive science, artificial intelligence, computer science, cognitive psychology, and neurocomputing, in keeping up-to-date with the newest research trends. It should provide a comprehensive introduction to this new emerging field.

Full Product Details

Author:   Ron Sun ,  Lawrence A. Bookman
Publisher:   Springer
Imprint:   Springer
Edition:   1995 ed.
Volume:   292
Dimensions:   Width: 15.50cm , Height: 2.60cm , Length: 23.50cm
Weight:   1.930kg
ISBN:  

9780792395171

ISBN 10:   0792395174
Pages:   476
Publication Date:   30 November 1994
Audience:   College/higher education ,  Professional and scholarly ,  Postgraduate, Research & Scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print  
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Table of Contents

Parallelism in inheritance hierarchies with exceptions.- An Introduction: On Symbolic Processing in Neural Networks.- Localist Architectures.- Complex Symbol-Processing in Conposit, A Transiently Localist Connectionist Architecture.- A Structured Connectionist Approach to Inferencing and Retrieval.- Hierarchical Architectures for Reasoning.- Distributed Architectures.- Subsymbolic Parsing of Embedded Structures.- Towards Instructable Connectionist Systems.- An Internal Report for Connectionists.- Combined Architectures.- A Two-Level Hybrid Architecture for Structuring Knowledge for Commonsense Reasoning.- A Framework for Integrating Relational and Associational Knowledge for Comprehension.- Examining a Hybrid Connectionist/Symbolic System for the Analysis of Ballistic Signals.- Commentaries.- Symbolic Artificial Intelligence and Numeric Artificial Neural Networks: Towards a Resolution of the Dichotomy.- Connectionist Natural Language Processing: A Status Report.

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