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 282
... Metaclasses Knowledge sources can be viewed as functions in the problem solving process ; the metaclasses are the arguments or roles in this process . A metaclass has therefore no structure ; it is a slot that can be filled with a ...
... Metaclasses Knowledge sources can be viewed as functions in the problem solving process ; the metaclasses are the arguments or roles in this process . A metaclass has therefore no structure ; it is a slot that can be filled with a ...
Page 283
... metaclasses is difficult to construct , because the structure of the problem solving process ( e.g. inference structure and task structure ) varies . Therefore , we have only used a very crude leading principle in viewing the problem ...
... metaclasses is difficult to construct , because the structure of the problem solving process ( e.g. inference structure and task structure ) varies . Therefore , we have only used a very crude leading principle in viewing the problem ...
Page 284
... metaclasses . A provisional is_a hierarchy of metaclasses , based upon the experiences in constructing the interpretation models is presented below . It is to be expected that this structure can be further refined . An important reason ...
... metaclasses . A provisional is_a hierarchy of metaclasses , based upon the experiences in constructing the interpretation models is presented below . It is to be expected that this structure can be further refined . An important reason ...
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