Knowledge representation plays a key role in the development of any Artificial Intelligence based system. A good representation can significantly shorten development time and execution speed, while a poor representation can doom a project.Four representation techniques are commonly used to model knowledge in expert systems: logic, production rules, semantic networks, and frames. This paper describes the application of each of these techniques in modelling mechanical systems. Advantages and disadvantages for each of these techniques are presented.


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    Titel :

    Knowledge Representation for Expert Systems: A Survey and Evaluation of Techniques


    Weitere Titelangaben:

    Sae Technical Papers


    Beteiligte:

    Kongress:

    SAE International Congress and Exposition ; 1987



    Erscheinungsdatum :

    01.02.1987




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




    Knowledge representation for expert systems:a survey and evaluation of techniques

    Dankel,D.D. / Univ.of Florida,Computer and Information Science,US | Kraftfahrwesen | 1987





    Knowledge Based Expert Systems in Transportation

    L. F. Cohn / R. A. Harris | NTIS | 1992