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
Results 1-5 of 89
Page 13
... types and size of knowledge involved in the application considered. Once the main features of problem domain have been precisely identified, its adequacy to expert system technology is verified. A precise identification of the problem ...
... types and size of knowledge involved in the application considered. Once the main features of problem domain have been precisely identified, its adequacy to expert system technology is verified. A precise identification of the problem ...
Page 14
... type of performance the full system will be capable of on a limited part of the considered problem. The demonstrator ... types of demonstrators may be identified, covering a full spectrum of possibilities ranging from explorative (first ...
... type of performance the full system will be capable of on a limited part of the considered problem. The demonstrator ... types of demonstrators may be identified, covering a full spectrum of possibilities ranging from explorative (first ...
Page 15
... type of the demonstrator to be developed. Then, from the whole problem to be solved, a limited subproblem is selected, on which the demonstrator will focus. Of course, the chosen subproblem must feature significant characteristics ...
... type of the demonstrator to be developed. Then, from the whole problem to be solved, a limited subproblem is selected, on which the demonstrator will focus. Of course, the chosen subproblem must feature significant characteristics ...
Page 17
... types of products featuring different technical characteristics. According to the choice taken, the target system is then developed and, as soon as it is completed, it is installed in the real operating environment. Extended field ...
... types of products featuring different technical characteristics. According to the choice taken, the target system is then developed and, as soon as it is completed, it is installed in the real operating environment. Extended field ...
Page 20
... types of methods to be included in a development methodology should cover (at least) the following topics: technique methods - technology methods, which indicate for each task or activity prescribed in the life cycle the available ...
... types of methods to be included in a development methodology should cover (at least) the following topics: technique methods - technology methods, which indicate for each task or activity prescribed in the life cycle the available ...
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 |
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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