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 167
... representation that will lead to the first implementation prototype of the system . The questions that immediately arise are the folowing : Do the types of problem solving involved make one particular representation a natural choice ...
... representation that will lead to the first implementation prototype of the system . The questions that immediately arise are the folowing : Do the types of problem solving involved make one particular representation a natural choice ...
Page 334
... representation stages in order to represent intermediate results of the total knowledge acquisition process , e.g. OPAL [ 21 ] and KADS [ 22 ] . An intermediate knowledge representation level is useful to maintain information closer to ...
... representation stages in order to represent intermediate results of the total knowledge acquisition process , e.g. OPAL [ 21 ] and KADS [ 22 ] . An intermediate knowledge representation level is useful to maintain information closer to ...
Page 335
... representation language is a set of propositions , consisting of primitives to describe the basic relations of concepts discovered by protocol analysis . These primitives are results of the protocol analysis . The set of primitives is ...
... representation language is a set of propositions , consisting of primitives to describe the basic relations of concepts discovered by protocol analysis . These primitives are results of the protocol analysis . The set of primitives is ...
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