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 120
... portion of the knowledge base is best suited to describing general properties or orga- nizational principles of the domain and not detailed problem solving . The network structures can provide partial orderings of goals to pursue and ...
... portion of the knowledge base is best suited to describing general properties or orga- nizational principles of the domain and not detailed problem solving . The network structures can provide partial orderings of goals to pursue and ...
Page 134
... portions of the graph that are instantiated at any given time . The instantiation ( or deinstantiation ) of portions ... portion of the CAE process is concerned with determining a valid place- ment within a building for the various items ...
... portions of the graph that are instantiated at any given time . The instantiation ( or deinstantiation ) of portions ... portion of the CAE process is concerned with determining a valid place- ment within a building for the various items ...
Page 135
... portions of sophisticated exert systems for real world problems must be encoded directly in a procedural language of ... portion of the solution to a complex problem . The theme of explicitly encoding problem solving control information ...
... portions of sophisticated exert systems for real world problems must be encoded directly in a procedural language of ... portion of the solution to a complex problem . The theme of explicitly encoding problem solving control information ...
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