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 30
... expertise from an expert . If domain expertise is easily available and inexpensive , there may be no need for an expert system development . How- ever , if the expertise is not or will not be available on a reliable and continuing ...
... expertise from an expert . If domain expertise is easily available and inexpensive , there may be no need for an expert system development . How- ever , if the expertise is not or will not be available on a reliable and continuing ...
Page 33
... expertise for the expert system . If the system is to perform at or near expert level , the project should get its expertise from one of the very best experts in the domain . • The expert's knowledge and reputation is such that the ...
... expertise for the expert system . If the system is to perform at or near expert level , the project should get its expertise from one of the very best experts in the domain . • The expert's knowledge and reputation is such that the ...
Page 266
... expertise remains implicit . With growing expertise the knowledge becomes automised and compiled out , and is no longer directly accessible for inspection . Minsky ( 1985 ) presents an illuminating , and somewhat more pessimistic ...
... expertise remains implicit . With growing expertise the knowledge becomes automised and compiled out , and is no longer directly accessible for inspection . Minsky ( 1985 ) presents an illuminating , and somewhat more pessimistic ...
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