Knowledge engineering for real time intelligent control

Issue title: Special Issue on Knowledge Engineering

Article type: Research Article

Authors: Messina, Elena R. | Albus, James S. | Schlenoff, Craig I. | Evans, John

Affiliations: Intelligent Systems Division, National Institute of Standards and Technology, 100 Bureau Drive, Stop 8230, Gaithersburg, MD 20899-8230, USA. Tel.: +1 301 975 3510; Fax: +1 301 990 9688; E-mail: {elena.messina, james.albus, craig.schlenoff}@nist.gov, [email protected]

Note: [] Corresponding author

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.

Journal: Journal of Intelligent & Fuzzy Systems, vol. 14, no. 3, pp. 137-147, 2003