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 224
... evaluation can be expected to be impartial . Intentional biases should be made explicit to avoid an evaluation's being used by unwitting consumers . For all but the most informal purposes , evaluation must be objective if it is to have ...
... evaluation can be expected to be impartial . Intentional biases should be made explicit to avoid an evaluation's being used by unwitting consumers . For all but the most informal purposes , evaluation must be objective if it is to have ...
Page 395
... evaluation although some of the results from that can be pertinent for calculating the effectiveness . But the problem of cost - effectiveness may be ... evaluation criteria , and the most important of Evaluation of expert systems 395.
... evaluation although some of the results from that can be pertinent for calculating the effectiveness . But the problem of cost - effectiveness may be ... evaluation criteria , and the most important of Evaluation of expert systems 395.
Page 407
... evaluation of each system in turn , but also a comparison between different versions of the same system ( cf. Pearce , 1988 ) , e.g. in performance tuning , or even between completely ... evaluation provides Evaluation of expert systems 407.
... evaluation of each system in turn , but also a comparison between different versions of the same system ( cf. Pearce , 1988 ) , e.g. in performance tuning , or even between completely ... evaluation provides Evaluation of expert systems 407.
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