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 51
... need to use non - ambiguous design specifications to communicate between work units is greatly diminished . 2.2.2 . Tool ... needs of a specific application . Thus , the flexibility to call - out to a more general purpose , though more ...
... need to use non - ambiguous design specifications to communicate between work units is greatly diminished . 2.2.2 . Tool ... needs of a specific application . Thus , the flexibility to call - out to a more general purpose , though more ...
Page 234
... needs to be defined more broadly . From a cognitive engineering perspective , knowledge acquisition is first about understanding the factors that make problem - solving in the domain hard ( for any agent human machine ) and how machine ...
... needs to be defined more broadly . From a cognitive engineering perspective , knowledge acquisition is first about understanding the factors that make problem - solving in the domain hard ( for any agent human machine ) and how machine ...
Page 369
... needs to determine all of the possible rules that could store a value for the attribute . To provide information about which rules use a particular attribute , the system needs to search the IF clauses of all of the rules to find those ...
... needs to determine all of the possible rules that could store a value for the attribute . To provide information about which rules use a particular attribute , the system needs to search the IF clauses of all of the rules to find those ...
Contents
From life cycle to development | 3 |
Choosing an expert system domain | 27 |
Tools and motivations | 47 |
Copyright | |
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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