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 57
Page viii
... expertise in knowledge acquisition Joost Breuker and Bob Wielinga A methodology and tool for knowledge acquisition in KEATS-2 Enrico Motta, Tim Rajan, and Marc Eisenstadt Knowledge-based knowledge elicitation Joachim Diederich and Marc ...
... expertise in knowledge acquisition Joost Breuker and Bob Wielinga A methodology and tool for knowledge acquisition in KEATS-2 Enrico Motta, Tim Rajan, and Marc Eisenstadt Knowledge-based knowledge elicitation Joachim Diederich and Marc ...
Page 30
... expertise from an expert. If domain expertise is easily available and inexpensive, there may be no need for an expert system development. However, if the expertise is not or will not be available on a reliable and continuing basis, then ...
... expertise from an expert. If domain expertise is easily available and inexpensive, there may be no need for an expert system development. However, if the expertise is not or will not be available on a reliable and continuing basis, then ...
Page 32
... difficult or very expensive for the expert system to produce or to deliver to the appropriate location, then this problem must be considered when evaluating the domain. 3. 3 Experts and Expertise • A top domain expert 32 D.S. Prerau.
... difficult or very expensive for the expert system to produce or to deliver to the appropriate location, then this problem must be considered when evaluating the domain. 3. 3 Experts and Expertise • A top domain expert 32 D.S. Prerau.
Page 33
... expertise for the expert system. If the system is to perform at or near expert level, the project should get its expertise from one of the very best experts in the domain. • The expert's knowledge and reputation is such that the expert ...
... expertise for the expert system. If the system is to perform at or near expert level, the project should get its expertise from one of the very best experts in the domain. • The expert's knowledge and reputation is such that the expert ...
Page 34
... expertise, but also the ability to impart it to the project team, whose members probably know little or nothing ... expertise for the system, at least that pertaining to one particular sub-domain, is to be obtained primarily from one ...
... expertise, but also the ability to impart it to the project team, whose members probably know little or nothing ... expertise for the system, at least that pertaining to one particular sub-domain, is to be obtained primarily from one ...
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