Evaluating Knowledge and Representation for Intelligent Control
Elena R. Messina, John Evans, James S. Albus
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.
September 4, 2001
Mexico City, MX
2001 Performance Metrics for Intelligent Systems (PerMIS)Workshop, in association with IEEE CCA and ISIC
, Evans, J.
and Albus, J.
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 March 4, 2024)