Topics in Expert System Design: Methodologies and ToolsC. Tasso, G. Guida Elsevier, 2014 M06 28 - 447 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.This book has a dual purpose: to offer concrete guidelines and tools to the designers of expert systems, and to promote basic and applied research on methodologies and tools. It is a coordinated collection of papers from researchers in the USA and Europe, examining important and emerging topics, methodological advances and practical experience obtained in specific applications. Each paper includes a survey introduction, and a comprehensive bibliography is provided. |
From inside the book
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Page 9
... contexts. - It should be flexible, i.e. easily adaptable to projects of different size and complexity. The second set of requirements is strictly specific to expert systems and derives from the need of taking into account the peculiar ...
... contexts. - It should be flexible, i.e. easily adaptable to projects of different size and complexity. The second set of requirements is strictly specific to expert systems and derives from the need of taking into account the peculiar ...
Page 51
... context within which elaborations and refinements appear natural. While one expects functional prototypes to draw on an assortment of representational and problem-solving devices in order to rapidly demonstrate functionality, design ...
... context within which elaborations and refinements appear natural. While one expects functional prototypes to draw on an assortment of representational and problem-solving devices in order to rapidly demonstrate functionality, design ...
Page 52
... context of demonstrated use. As a result, it is necessary to engineer expertise into a system (knowledge engineering), and then run test cases to get an expert's assessment of performance and an explanation for errors. After tests of ...
... context of demonstrated use. As a result, it is necessary to engineer expertise into a system (knowledge engineering), and then run test cases to get an expert's assessment of performance and an explanation for errors. After tests of ...
Page 54
... context of a diagnostic application, for instance, the data-driven characteristic of OPS might be exploited to generate hypotheses on the basis of observed symptoms. The goal-driven, or proof-oriented, approach to problem solving ...
... context of a diagnostic application, for instance, the data-driven characteristic of OPS might be exploited to generate hypotheses on the basis of observed symptoms. The goal-driven, or proof-oriented, approach to problem solving ...
Page 62
... -OPS knowledge Source is activated. R3NOVV.E.DGE CFAFT Current context: ; RJD -Col Exo strif I. |Jed 15 Jur. 5:13:38] BRUER Ct): User Inout Figure 5-4: Application Specific Interface Figure 5-5: KC Network Editor. 62 G.S. Kahn and M. Bauer.
... -OPS knowledge Source is activated. R3NOVV.E.DGE CFAFT Current context: ; RJD -Col Exo strif I. |Jed 15 Jur. 5:13:38] BRUER Ct): User Inout Figure 5-4: Application Specific Interface Figure 5-5: KC Network Editor. 62 G.S. Kahn and M. Bauer.
Contents
25 | |
45 | |
Development tools | 179 |
Knowledge acquisition and modeling | 231 |
Validation and evaluation | 351 |
Further reading | 417 |
A STRUCTURED BIBLIOGRAPHY | 419 |
LIST OF CONTRIBUTORS | 437 |
AUTHOR INDEX | 441 |
Other editions - View all
Topics in Expert System Design: Methodologies and Tools Giovanni Guida,Carlo Tasso Snippet view - 1989 |
Common terms and phrases
abstract activities AI Magazine application approach Artificial Intelligence attribute backward chaining behavior Breuker Building Expert Systems cognitive complete components Computer concepts conceptual model construction context cycle decision defined described diagnosis domain expert domain knowledge environment example Expert System Design expert system development expert system evaluation expert system technology expertise facilities Figure formal function goal graphical heuristics identified implementation important inductive inference input instance integrated interaction interface 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 performance phase problem solving Proc programming Prolog protocol analysis prototype refinement relations reliability repertory grid represent requirements rule-based rules selection shells software engineering solution specific strategies structure task techniques Topics in Expert types validity values