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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

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


    Additional title:

    Sae Technical Papers


    Contributors:

    Conference:

    SAE International Congress and Exposition ; 1987



    Publication date :

    1987-02-01




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English




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

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