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 219
... important in the initial stages of tool use , peaking during the prototyping phase . As implementation decisions get locked in , flexibility decreases in importance and may actually become a negative factor in later phases as the need ...
... important in the initial stages of tool use , peaking during the prototyping phase . As implementation decisions get locked in , flexibility decreases in importance and may actually become a negative factor in later phases as the need ...
Page 225
... important to determine project characteristics at this point , defining the goals , scope and budget of the development effort , and characterizing the development team and development environment . The scope of the project determines ...
... important to determine project characteristics at this point , defining the goals , scope and budget of the development effort , and characterizing the development team and development environment . The scope of the project determines ...
Page 398
... important . The reasoning may be formally correct , but it may not be understandable to the user of the system . Since , however , an important part of the expert system's functioning is the interaction with the user - and since ...
... important . The reasoning may be formally correct , but it may not be understandable to the user of the system . Since , however , an important part of the expert system's functioning is the interaction with the user - and since ...
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