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 174
... economic , social , and individual payoffs ( and trade - offs ) will constitute the general parameters of an evaluation . Because the future of the system will often depend on the outcome of the evaluation , it is important to not only ...
... economic , social , and individual payoffs ( and trade - offs ) will constitute the general parameters of an evaluation . Because the future of the system will often depend on the outcome of the evaluation , it is important to not only ...
Page 175
... economic gain may suffice to demonstrate the advantages of the technological solution . However , because of the social repercussions of automation , and the ethical concerns about the correct application of codified human judgments ...
... economic gain may suffice to demonstrate the advantages of the technological solution . However , because of the social repercussions of automation , and the ethical concerns about the correct application of codified human judgments ...
Page 431
... economic assessment . This section deals with a topic of increasing interest in expert system technology , namely the validation and evaluation of expert system applications . This is a rather new area , but , nevertheless , it has been ...
... economic assessment . This section deals with a topic of increasing interest in expert system technology , namely the validation and evaluation of expert system applications . This is a rather new area , but , nevertheless , it has been ...
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