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 92
Page v
... Expert systems have in fact disclosed a new perspective on information processing, where the computer is considered ... Building expert systems still relies today on empirical approaches and it is more like handicraft than engineering ...
... Expert systems have in fact disclosed a new perspective on information processing, where the computer is considered ... Building expert systems still relies today on empirical approaches and it is more like handicraft than engineering ...
Page vi
... expert system designers who like to keep up to date with the current state-ofthe-art in the field. From a broader perspective, it is aimed at promoting basic and applied research on ... Building expert systems: From life vi Preface.
... expert system designers who like to keep up to date with the current state-ofthe-art in the field. From a broader perspective, it is aimed at promoting basic and applied research on ... Building expert systems: From life vi Preface.
Page vii
... Building expert systems: From life cycle to development methodology Giovanni Guida and Carlo Tasso Part 2. Domain evaluation Choosing an expert system domain David S. Prerau Part 3. Design techniques 27 Prototyping: Tools and ...
... Building expert systems: From life cycle to development methodology Giovanni Guida and Carlo Tasso Part 2. Domain evaluation Choosing an expert system domain David S. Prerau Part 3. Design techniques 27 Prototyping: Tools and ...
Page viii
... expert systems Erik Hollnagel Part 7. Further reading 353 377 Building expert systems: A structured bibliography Giovanni Guida and Carlo Tasso List of contributors 4. 19 437 Topics in Expert System Design G. Guida and C. Tasso. Author ...
... expert systems Erik Hollnagel Part 7. Further reading 353 377 Building expert systems: A structured bibliography Giovanni Guida and Carlo Tasso List of contributors 4. 19 437 Topics in Expert System Design G. Guida and C. Tasso. Author ...
Page 3
Methodologies and Tools C. Tasso, G. Guida. Topics in Expert System Design G. Guida and C. Tasso (Editors) © Elsevier Science Publishers B.V. (North-Holland), 1989 3 BUILDING EXPERT SYSTEMS: FROM LIFE CYCLE TO DEVELOPMENT METHODOLOGY ...
Methodologies and Tools C. Tasso, G. Guida. Topics in Expert System Design G. Guida and C. Tasso (Editors) © Elsevier Science Publishers B.V. (North-Holland), 1989 3 BUILDING EXPERT SYSTEMS: FROM LIFE CYCLE TO DEVELOPMENT METHODOLOGY ...
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