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 at 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 andsymbolic 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), theirstrengths and weaknesses,
why they work, and what they predict, and (2) a critique/comparison of
these approaches.
The book will be of use toresearchers, graduate
students, and interested laymen, in areas such as
cognitive science, artificial
intelligence, computer science, cognitivepsychology, and neurocomputing,
in keeping up to date with the newest researchtrends. It can also serve
as a comprehensive, in-depth introduction to thisnew 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 and 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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To order:
ISBN 0-7923-9517-4
Kluwer, Order Dept.
P.O.B. 358
Accord Station, Hingham, MA 02018-0358
(617) 871-6600
FAX: (617) 871-6528
e-mail: Kluwer@world.std.com
http://kapis.www.wkap.nl/book.htm/0-7923-9517-4
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