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 5
... planning , and technology transfer . Waterman's ( 1986 ) work is inspired , especially for its focus on knowledge acquisition tasks , to ( Buchanan , Barstow , Bechtel , Bennett , Clancey , Kulikowski , Mitchell , and Waterman , 1983 ) ...
... planning , and technology transfer . Waterman's ( 1986 ) work is inspired , especially for its focus on knowledge acquisition tasks , to ( Buchanan , Barstow , Bechtel , Bennett , Clancey , Kulikowski , Mitchell , and Waterman , 1983 ) ...
Page 10
... planning and control of project advancements is widely recognized as a major exigency for an industrial applicability of expert system technology . As an expert system is a kind of software product , it is natural that the first step ...
... planning and control of project advancements is widely recognized as a major exigency for an industrial applicability of expert system technology . As an expert system is a kind of software product , it is natural that the first step ...
Page 161
... Planning · Integrating an expert system into the routine provision of health care is not easy , and an alternative ... planning tasks . Several graphical summarization and knowledge acquisition techniques have been made available so that ...
... Planning · Integrating an expert system into the routine provision of health care is not easy , and an alternative ... planning tasks . Several graphical summarization and knowledge acquisition techniques have been made available so that ...
Contents
From life cycle to development | 3 |
Choosing an expert system domain | 27 |
Tools and motivations | 47 |
Copyright | |
14 other sections not shown
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abstract activities AI Magazine application approach Artificial Intelligence assessment attribute backward chaining behavior Breuker building cognitive complete components Computer concepts conceptual model construction context cycle decision defined described diagnosis domain expert domain knowledge environment example expert system development expert system evaluation expert system technology expertise facilities Figure formal function goal graphical heuristics identified implementation important inductive input instance integrated interaction interface interpretation models KADS KCML knowledge acquisition knowledge base Knowledge Craft knowledge elicitation knowledge engineer knowledge representation knowledge-based systems KRITON language layer LISP machine machine learning metaclasses methodology methods model-based reasoning MYCIN objects operations OPS5 output particular performance phase possible problem solving problem solving process produce programming Prolog protocol analysis prototype refinement relations reliability repertory grid represent requirements rule-based rules selection shells situations software engineering solution specific strategies target system task techniques types validity values