Artificial Intelligence and Neural Networks
Steps Toward Principled Integration
Academic Press
Published on 1. January 1994
Book
Hardback
664 pages
978-0-12-355055-2 (ISBN)
Description
Traditional artificial intelligence and neural networks are generally considered appropriate for solving different types of problems. On the surface these networks 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. This volume presents a critical examination of the key issues, underlying assumptions, and suggestions related to the reconciliation and principled integration of artificial intelligence and neural networks. Examples of this integration for a variety of specific applications are outlined. The text also provides an introduction to the basics of symbol processing, connectionist networks, and their integration.
More details
Series
Language
English
Place of publication
San Diego
United States
Publishing group
Elsevier Science Publishing Co Inc
Target group
College/higher education
Professional and scholarly
Illustrations
index
Dimensions
Height: 234 mm
Width: 155 mm
Weight
1053 gr
ISBN-13
978-0-12-355055-2 (9780123550552)
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Schweitzer Classification
Content
Symbol Processors Versus Connectionist Networks. Representation and Inference. Vision. Language. Learning.