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Computational Architectures Integrating Neural and Symbolic Processes

A Perspective on the State of the Art

  • Book
  • © 1995

Overview

Editors:
  1. Ron Sun

    1. The University of Alabama, Tuscaloosa, USA

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    You can also search for this editor in PubMed   Google Scholar

  2. Lawrence A. Bookman

    1. Sun Microsystems Laboratories, Chelmsford, USA

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    You can also search for this editor in PubMed   Google Scholar

Part of the book series: The Springer International Series in Engineering and Computer Science (SECS, volume 292)

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Table of contents (12 chapters)

  1. Front Matter

    Pages i-xviii
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  2. Parallelism in inheritance hierarchies with exceptions

    1. An Introduction: On Symbolic Processing in Neural Networks

      • Ron Sun
      Pages 1-18

  3. Localist Architectures

    1. Front Matter

      Pages 19-20
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    2. Complex Symbol-Processing in Conposit, A Transiently Localist Connectionist Architecture

      • John A. Barnden
      Pages 21-68

    3. A Structured Connectionist Approach to Inferencing and Retrieval

      • Trent E. Lange
      Pages 69-115

    4. Hierarchical Architectures for Reasoning

      • R. C. Lacher, K. D. Nguyen
      Pages 117-150

  4. Distributed Architectures

    1. Front Matter

      Pages 151-152
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    2. Subsymbolic Parsing of Embedded Structures

      • Risto Miikkulainen
      Pages 153-186

    3. Towards Instructable Connectionist Systems

      • David C. Noelle, Garrison W. Cottrell
      Pages 187-221

    4. An Internal Report for Connectionists

      • Noel E. Sharkey, Stuart A. Jackson
      Pages 223-244

  7. Back Matter

    Pages 431-475
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Keywords

About this book

Computational Architectures Integrating Neural and Symbolic Processes: A Perspective on the State of the Art focuses on a currently emerging body of research. With the reemergence 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.
Computational Architectures Integrating Neural and Symbolic Processes 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.
Computational Architectures Integrating Neural and Symbolic Processes is 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 is a comprehensive, in-depth introduction to this new emerging field.

Editors and Affiliations

  • The University of Alabama, Tuscaloosa, USA

    Ron Sun

  • Sun Microsystems Laboratories, Chelmsford, USA

    Lawrence A. Bookman

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