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PUBLICATIONS

Knowledge Engineering for Real Time Intelligent Control

Published

Author(s)

Elena R. Messina, James S. Albus, Craig I. Schlenoff, J L. Evans

Abstract

The key to real-time intelligent control lies in the knowledge models that the system contains. We argue that there needs to be a more rigorous approach to engineering the knowledge within intelligent controllers. Three main classes of knowledge are identified: parametric, geometric/iconic, and symbolic. Each of these classes provides unique perspectives and advantages for the planning of behaviors by the intelligent system. Examples of each from demonstration systems are presented.
Citation
Journal of Intelligent & Fuzzy Systems
Volume
14
Pub Type
Journals

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Keywords

geometic, iconic, intelligent control, Knowledge Engineering, knowledge representation, parametic, Robotics & Intelligent Systems, spatial, Unmanned System

Citation

Messina, E. , Albus, J. , Schlenoff, C. and Evans, J. (2003), Knowledge Engineering for Real Time Intelligent Control, Journal of Intelligent & Fuzzy Systems, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822497 (Accessed December 15, 2024)

Issues

If you have any questions about this publication or are having problems accessing it, please contact reflib@nist.gov.

Created December 31, 2003, Updated February 17, 2017