Topics in Expert System Design: Methodologies and ToolsGiovanni Guida, Carlo Tasso North-Holland, 1989 - 441 pages Expert Systems are so far the most promising achievement of artificial intelligence research. Decision making, planning, design, control, supervision and diagnosis are areas where they are showing great potential. However, the establishment of expert system technology and its actual industrial impact are still limited by the lack of a sound, general and reliable design and construction methodology. |
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Page 173
... performance and intelligently suggesting refinements of the knowledge base . It was most successful in helping build and refine the AI / RHEUM knowledge base , and also served an independent research group at the University of Missouri ...
... performance and intelligently suggesting refinements of the knowledge base . It was most successful in helping build and refine the AI / RHEUM knowledge base , and also served an independent research group at the University of Missouri ...
Page 249
... performance modeling can vary from informal interviews , retrospective analyses of actual incidents ( Flanagan , 1954 ; Klein , in press ) , observation of practitioners as they attempt to perform domain task ( e.g. , Bainbridge , 1979 ...
... performance modeling can vary from informal interviews , retrospective analyses of actual incidents ( Flanagan , 1954 ; Klein , in press ) , observation of practitioners as they attempt to perform domain task ( e.g. , Bainbridge , 1979 ...
Page 405
... performance on the system , using the performance of internists as a reference . Another case was the development of a prototype expert system for credit evaluation ( Ben & Sterling , 1985 ) , where the performance was evaluated by ...
... performance on the system , using the performance of internists as a reference . Another case was the development of a prototype expert system for credit evaluation ( Ben & Sterling , 1985 ) , where the performance was evaluated by ...
Contents
From life cycle to development | 3 |
Choosing an expert system domain | 27 |
Tools and motivations | 47 |
Copyright | |
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abstract activities addition allow analysis application approach attribute building complete components Computer concepts conclusion considered consists construction contains decision defined depends described detailed discussed domain effective elicitation environment evaluation example expert system expertise facilities fact Figure formal frame function given goal human identified implementation important inference input instance integrated Intelligence interaction interface International interpretation knowledge acquisition knowledge base knowledge engineer knowledge representation knowledge-based language learning limited machine major means mechanisms methodology methods objects operations output particular performance phase possible practical presented problem solving produce programming Prolog prototype question reasoning refer refinement relations Report represent representation requirements rules selection shells shows situations solution specific strategies structure studies system development task techniques types validity values