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 115
... knowledge bases regardless of their source . 4 . INTEGRATED APPROACH TO KNOWLEDGE - BASED SYSTEMS The expert system shells currently in the marketplace are predominantly built upon the expert systems research of the middle to late 1970s ...
... knowledge bases regardless of their source . 4 . INTEGRATED APPROACH TO KNOWLEDGE - BASED SYSTEMS The expert system shells currently in the marketplace are predominantly built upon the expert systems research of the middle to late 1970s ...
Page 135
... based systems with those of object oriented programming . This combination enables a high degree of control and ... Knowledge - based Systems The integrated approach described here is of little value unless all of its components can be ...
... based systems with those of object oriented programming . This combination enables a high degree of control and ... Knowledge - based Systems The integrated approach described here is of little value unless all of its components can be ...
Page 162
... knowledge - based systems , it was recognized that extracting the knowledge from an expert was difficult and usually produced the greatest delays in building a knowledge base . The TEIRESIAS system [ 30 ] developed as early as 1975 by ...
... knowledge - based systems , it was recognized that extracting the knowledge from an expert was difficult and usually produced the greatest delays in building a knowledge base . The TEIRESIAS system [ 30 ] developed as early as 1975 by ...
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