Monograph: SaarbrΓΌcken, Germany. - Publisher AV Akademikerverlag GmbH& Co. KG (LAP LAMBERT Academic Publishing), 2012. - 226 p.<div class="bb-sep"></div>The book reveals complex cross-cutting issues of estimation uncertainty and certainty, analysis and management in the socio-economic systems, inclu
Managing Uncertainty in Expert Systems
β Scribed by Jerzy W. Grzymala-Busse (auth.)
- Publisher
- Springer US
- Year
- 1991
- Tongue
- English
- Leaves
- 241
- Series
- The Springer International Series in Engineering and Computer Science 143
- Edition
- 1
- Category
- Library
No coin nor oath required. For personal study only.
β¦ Synopsis
3. Textbook for a course in expert systems,if an emphasis is placed on Chapters 1 to 3 and on a selection of material from Chapters 4 to 7. There is also the option of using an additional commercially available sheU for a programming project. In assigning a programming project, the instructor may use any part of a great variety of books covering many subjects, such as car repair. Instructions for mostofthe "weekend mechanic" books are close stylisticaUy to expert system rules. Contents Chapter 1 gives an introduction to the subject matter; it briefly presents basic concepts, history, and some perspectives ofexpert systems. Then itpresents the architecture of an expert system and explains the stages of building an expert system. The concept of uncertainty in expert systems and the necessity of dealΒ ing with the phenomenon are then presented. The chapter ends with the descripΒ tion of taxonomy ofexpert systems. Chapter 2 focuses on knowledge representation. Four basic ways to repreΒ sent knowledge in expert systems are presented: first-order logic, production sysΒ tems, semantic nets, and frames. Chapter 3 contains material about knowledge acquisition. Among machine learning techniques, a methodofrule learning from examples is explained in deΒ tail. Then problems ofrule-base verification are discussed. In particular, both consistency and completeness oftherule base are presented.
β¦ Table of Contents
Front Matter....Pages i-xxi
Introduction....Pages 1-12
Knowledge Representation....Pages 13-42
Knowledge Acquisition....Pages 43-76
One-Valued Quantitative Approaches....Pages 77-102
Two-Valued Quantitative Approaches....Pages 103-126
Set-Valued Quantitative Approaches....Pages 127-180
Qualitative Approaches....Pages 181-207
Back Matter....Pages 209-224
β¦ Subjects
Artificial Intelligence (incl. Robotics); Mathematical Logic and Foundations
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