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. |
From inside the book
Results 1-3 of 27
Page 20
... practice in an effective , efficient and controlled way . This involves three main aspects : · - refining the life cycle through the identification , for each phase , of appropriate tasks and activities ( task and activity definition ) ...
... practice in an effective , efficient and controlled way . This involves three main aspects : · - refining the life cycle through the identification , for each phase , of appropriate tasks and activities ( task and activity definition ) ...
Page 37
... practices , embodied in heuristics , that may prove embarrassing if written down . For example , unwritten rules concerning how certain customers are treated relative to other customers . But if an expert system is to be developed ...
... practices , embodied in heuristics , that may prove embarrassing if written down . For example , unwritten rules concerning how certain customers are treated relative to other customers . But if an expert system is to be developed ...
Page 289
... practice outside the KADS project . A number of major knowledge engineering companies in the Netherlands have adopted and adapted KADS for their standard practice ( e.g. van Lith , 1987 ) . Here we can only summarise some of the major ...
... practice outside the KADS project . A number of major knowledge engineering companies in the Netherlands have adopted and adapted KADS for their standard practice ( e.g. van Lith , 1987 ) . Here we can only summarise some of the major ...
Contents
From life cycle to development | 3 |
Choosing an expert system domain | 27 |
Tools and motivations | 47 |
Copyright | |
14 other sections not shown
Other editions - View all
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