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 51
... Implementation Prototypes Once a design is articulated , implementation can begin . While a design may change during the implementation phase , it is desirable to distinguish between design prototypes that serve exploratory purposes and ...
... Implementation Prototypes Once a design is articulated , implementation can begin . While a design may change during the implementation phase , it is desirable to distinguish between design prototypes that serve exploratory purposes and ...
Page 291
... implementation directly follows the analysis , and the conceptual model is used more or less as an architecture of the system . In most of the recent studies , a Design phase follows . No revisiting of the analysis phase from the design ...
... implementation directly follows the analysis , and the conceptual model is used more or less as an architecture of the system . In most of the recent studies , a Design phase follows . No revisiting of the analysis phase from the design ...
Page 305
... implementation leads to a view of knowledge acquisition as the production of an abstract architecture that is distinct from the implementation of the system . This view has some advantages that include the factorization of the tasks and ...
... implementation leads to a view of knowledge acquisition as the production of an abstract architecture that is distinct from the implementation of the system . This view has some advantages that include the factorization of the tasks and ...
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