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.
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