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Evaluating Knowledge and Representation for Intelligent Control

Published

Author(s)

Elena R. Messina, John Evans, James S. Albus

Abstract

Knowledge and the way it is represented have a tremendous impact on the capabilities and performance of intelligent systems. There is evidence from studies of human cognitive functions that experts use multiple representations in problem solving tasks and know when to switch between representations. In this paper, we discuss the issues pertaining to what types of knowledge are required for an intelligent system, how to evaluate the knowledge and representations, and provide examples of how representation affects and even enables functionality of a system. We describe an example of an intelligent system architecture that is built upon multiple knowledge types and representations and has been applied to a variety of real-time intelligent systems.
Conference Dates
September 4, 2001
Conference Location
Mexico City, MX
Conference Title
2001 Performance Metrics for Intelligent Systems (PerMIS)Workshop, in association with IEEE CCA and ISIC

Keywords

intelligent control, intelligent control, intelligent control, intelligent systems, intelligent systems, intelligent systems, knowledge representation, knowledge representation, knowledge representation, performance evaluation, performance evaluation, performance evaluation, performance metrics, performance metrics, performance metrics, world modeling, world modeling, world modeling

Citation

Messina, E. , Evans, J. and Albus, J. (2001), Evaluating Knowledge and Representation for Intelligent Control, 2001 Performance Metrics for Intelligent Systems (PerMIS)Workshop, in association with IEEE CCA and ISIC, Mexico City, MX, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=821637 (Accessed July 21, 2024)

Issues

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Created September 4, 2001, Updated February 17, 2017