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Proceedings Paper

Styles Of Programming In Neural Networks And Expert Systems
Author(s): Richard O. Duda
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Paper Abstract

Neural networks and expert systems provide different ways to reduce the programming effort required to build complex systems. Adaptive neural networks are programmed merely by training them with examples. Rule-based expert system are developed incrementally merely by adding rules. Although neural networks seem best suited for low-level sensory processing and expert systems seem best suited for high-level symbolic processing, strikingly similar issues arise when these approaches are used in large-scale applications. Illustrative examples of such applications are presented and discussed.

Paper Details

Date Published: 21 March 1989
PDF: 10 pages
Proc. SPIE 1095, Applications of Artificial Intelligence VII, (21 March 1989); doi: 10.1117/12.969304
Show Author Affiliations
Richard O. Duda, San Jose State University (United States)


Published in SPIE Proceedings Vol. 1095:
Applications of Artificial Intelligence VII
Mohan M. Trivedi, Editor(s)

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