Artificial Intelligence and Neural Networks:
Steps Toward Principled Integration

Vasant Honavar and Leonard Uhr (Ed.)
Boston: Academic Press (1994).
ISBN 0-12-355055-6, 653+xxxii pages
Currently marketed by Elsevier and can be ordered from Barnes and Noble or Amazon.



Summary

Traditional artificial intelligence and neural networks are generally considered appropriate for solving different types of problems. On the surface these two approaches appear to be very different, but a growing body of current research is focused on how the strengths of each can be incorporated into the other and built into systems that include the best features of both. Artificial Intelligence and Neural Networks: Steps Toward Principled Integration is a critical examination of the key issues, underlying assumptions and suggestions related to the reconciliation and principled integration of artificial intelligence and neural networks. With contributions from leading researchers in the field, this comprehensive text provides a thorough introduction to the basics of symbol processing, connectionist networks and their integration. Numerous examples of the integration of artificial intelligence and neural networks for a variety of specific applications provide unique insight into this evolving area.


Table of Contents


Vasant Honavar
Artificial Intelligence Research Group
Department of Computer Science and
Interdepartmental Program in Neuroscience
210 Atanasoff Hall
Iowa State University
Ames, Iowa 50011-1040
voice: (515) 294-1098
fax: (515) 294-0258
email: honavar@cs.iastate.edu