Evaluating Knowledge and Representation for Intelligent Control
NATIONAL INST OF STANDARDS AND TECHNOLOGY GAITHERSBURG MD INTELLIGENT SYSTEMS DIV
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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.
- Computer Programming and Software