New Book

 ***  Announcing a new book ***
      available from Kluwer Academic Publishers:

COMPUTATIONAL ARCHITECTURES INTEGRATING NEURAL AND SYMBOLIC PROCESSES: A
PERSPECTIVE ON THE STATE OF THE ART

 Edited by Ron Sun and Larry Bookman

 ISBN 0-7923-9517-4

(Order information is in the end of this message)


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The focus of this book is on a currently emerging body of research ---
computational architectures integrating neural and symbolic processes. 
There has been a great deal of work in integrating neural and
symbolic processes, both from a cognitive and/or applicational viewpoint,
The editors of this book intend to  address the underlying
architectural aspects of this integration. In order to provide a basis for a
deeper understanding of existing divergent approaches and provide insight for
further developments in this field, the 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.  

The book will be of use 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 can also serve as a comprehensive, in-depth introduction to this
new emerging field. A unique feature of the book is a comprehensive
bibliography at the end of the book.


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TABLE OF CONTENTS

Foreword 
     by Michael Arbib

Preface
     by Ron Sun and Larry Bookman

Chapter 1	An Introduction: On Symbolic Processing in Neural Networks 
                by Ron Sun
  	Introduction
	Brief Review
	Existing Approaches
	Issues band Difficulties
	Future Directions, Or Where Should We Go From Here?
	Overview of the Chapters
	Summary

Part I		Localist Architectures

Chapter 2	Complex Symbol-Processing in Conposit, A Transiently Localist
		Connectionist Architecture by John A. Barnden
	Introduction
	The Johnson-Laird Theory and Its Challenges
	Mental Models in Conposit
 	Connectionist Realization of Conposit
	Coping with the Johnson-Laird Challenge
	Simulation Runs
	Discussion
	Summary

Chapter 3	A Structured Connectionist Approach to Inferencing and
		Retrieval by Trent E. Lange
	Introduction
	Language Understanding and Memory Retrieval Models
	Inferencing in ROBIN
	Episodic Retrieval in REMIND
	Future Work
	Summary

Chapter 4	Hierarchical Architectures for Reasoning
		by R.C. Lacher and K.D. Nguyen 
	Introduction
	Computational Networks: A General Setting for Distributed 
		Computations
 	Type x00 Computational Networks
	Expert Systems
	Expert Networks
	Neural Networks
	Summary

Part II Distributed Architectures

Chapter 5	Subsymbolic Parsing of Embedded Structures by Risto Miikkulainen
	Introduction
	Overview of Subsymbolic Sentence Processing
	The SPEC Architecture
	Experiments
	Discussion
 	Summary

Chapter 6	Towards Instructable Connectionist Systems 
		by David C. Noelle and Garrison W. Cottrell
	Introduction
	Systematic Action
	Linguistic Interaction
	Learning By Instruction
	Summary

Chapter 7	An Internal Report for Connectionists
		by Noel E. Sharkey and Stuart A. Jackson
	Introduction
 	The Origins of Connectionist Representation
	Representation and Decision Space
	Discussion
	Summary

Part III	Combined Architectures

Chapter 8	A Two-Level Hybrid Architecture for Structuring Knowledge for
		Commonsense Reasoning 
        by Ron Sun
 	Introduction
	Developing A Two-Level Architecture
	Fine-Tuning the Structure
	Experiments
 	Comparisons with Other Approaches
 	Summary
	
Chapter 9	A Framework for Integrating Relational and Associational
		Knowledge for Comprehension by Lawrence A. Bookman
	Introduction
 	Overview of LeMICON
	Text Comprehension
	Encoding Semantic Memory
	Representation of Semantic Constraints
	Experiments and Results
	Algorithm
	Summary

Chapter 10	Examining a Hybrid Connectionist/Symbolic System for the
		Analysis of Ballistic Signals by Charles Lin and James Hendler
	Introduction
	Related Work in Hybrid Systems
	Description of the SCRuFFY Architecture
	Analysis of Ballistic Signals
	Future Work
	Conclusion

Part  IV	Commentaries

Chapter 11	Symbolic Artificial Intelligence and Numeric Artificial Neural
		Networks: Towards a Resolution of the Dichotomy 
		by Vasant Honavar
	Introduction
	Shared Foundations of SAI and NANN
	Knowledge Representation Revisited
	A Closer Look at SAI and NANN
	Integration of SAI and NANN
	Summary

Chapter 12	Connectionist Natural Language Processing: A Status Report
		by Michael G. Dyer
	Introduction
	Dynamic Bindings
	Functional Bindings and Structured Pattern Matching
	Encoding and Accessing Recursive Structures
	Forming Lexical Memories
	Forming Semantic and Episodic Memories
	Role of Working Memory
	Routing and Control
	Grounding Language in Perception
 	Future Directions
 	Conclusions

Appendix 	Bibliography of Connectionist Models with Symbolic Processing
Author Index
Subjct Index


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 ISBN 0-7923-9517-4

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 P.O.B. 358
 Accord Station, Hingham, MA 02018-0358

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 FAX: (617) 871-6528

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