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 5
... consideration of a development process divided into phases , each one described only at a very high level of abstraction ... considerations motivate the appearance of specific methodological proposals , experimented in real application ...
... consideration of a development process divided into phases , each one described only at a very high level of abstraction ... considerations motivate the appearance of specific methodological proposals , experimented in real application ...
Page 170
... consideration " selling " the prototype to the expert should not be a primary consideration by this stage , unless they have opposed the system all along . 6.6 . In - House Critique Phase The first efforts at evaluation should always be ...
... consideration " selling " the prototype to the expert should not be a primary consideration by this stage , unless they have opposed the system all along . 6.6 . In - House Critique Phase The first efforts at evaluation should always be ...
Page 213
... consideration in choosing a tool , just as the availability of subroutine libraries for statistics , graphics , or database access is a consideration in choosing a programming language . Problem to be solved within the domain . The ...
... consideration in choosing a tool , just as the availability of subroutine libraries for statistics , graphics , or database access is a consideration in choosing a programming language . Problem to be solved within the domain . The ...
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