A basic paradigm that allows representation of physical systems with a focus on context and time is presented. Paragon provides the capability to quickly capture an expert's knowledge in a cognitively resonant manner. From that description, Paragon creates a simulation model in LISP, which when executed, verifies that the domain expert did not make any mistakes. The Achille's heel of rule-based systems has been the lack of a systematic methodology for testing, and Paragon's developers are certain that the model-based approach overcomes that problem. The reason this testing is now possible is that software, which is very difficult to test, has in essence been transformed into hardware.


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    Title :

    Temporal and contextual knowledge in model-based expert systems


    Contributors:


    Publication date :

    1987-11-01


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English




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