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 188
... facilities , explanation facilities , uncertainty handling and other system debugging facilities . Examples of such systems include APES ( Hammond and Sergot [ 33 ] ) and YAPES ( Niblett [ 34 ] ) . This type of tool appeals to the ...
... facilities , explanation facilities , uncertainty handling and other system debugging facilities . Examples of such systems include APES ( Hammond and Sergot [ 33 ] ) and YAPES ( Niblett [ 34 ] ) . This type of tool appeals to the ...
Page 194
... facilities offered vary markedly and the price ranges from a few hundred pounds to over ten thousand pounds . Mainframe or VAX shells cost a lot more than the PC shells but , of course , they can be run on many distributed terminals ...
... facilities offered vary markedly and the price ranges from a few hundred pounds to over ten thousand pounds . Mainframe or VAX shells cost a lot more than the PC shells but , of course , they can be run on many distributed terminals ...
Page 195
... facilities . Some of the smaller ones offer only attribute - value pairs , simple sets and rules to process them . More sophisticated shells allow variables in rules ( for example Xi Plus or APES ) , and simple hierarchical structures ...
... facilities . Some of the smaller ones offer only attribute - value pairs , simple sets and rules to process them . More sophisticated shells allow variables in rules ( for example Xi Plus or APES ) , and simple hierarchical structures ...
Contents
From life cycle to development | 3 |
Choosing an expert system domain | 27 |
Tools and motivations | 47 |
Copyright | |
14 other sections not shown
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Common terms and phrases
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