Systematic Introduction to Expert Systems
Knowledge Representations and Problem-Solving Methods
(Sprache: Englisch)
At present one of the main obstacles to a broaderapplication of expert systems is the lack of a theory totell us which problem-solving methods areavailable for agiven problem class. Such a theory could lead to significantprogress in the following central...
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At present one of the main obstacles to a broaderapplication of expert systems is the lack of a theory totell us which problem-solving methods areavailable for agiven problem class. Such a theory could lead to significantprogress in the following central aims of the expert systemtechnique:- Evaluating the technical feasibility of expert systemprojects: This depends on whether there is a suitableproblem-solving method, and if possible a correspondingtool, for the given problem class.- Simplifying knowledge acquisition and maintenance: Theproblem-solving methods provide direct assistance asinterpretation models in knowledge acquisition. Also, theymake possible the development of problem-specific expertsystem tools with graphical knowledge acquisitioncomponents, which can be used even by experts withoutprogramming experience.- Making use of expert systems as a knowledge medium: Thestructured knowledge in expert systems can be used not onlyfor problem solving but also for knowledge communication andtutorial purposes.With such a theory in mind, this book provides a systematicintroduction to expert systems. It describes the basicknowledge representations and the present situation withregard tothe identification, realization, and integrationof problem-solving methods for the main problem classes ofexpert systems: classification (diagnostics), construction,and simulation.
Inhaltsverzeichnis zu „Systematic Introduction to Expert Systems “
I Introduction.- 1 Characterization and History of Expert Systems.- 2 Programming Languages and Expert System Tools.- 3 Use and Usability of Expert Systems.- II Basic Techniques of Knowledge Representation.- 4 Logic.- 5 Rules.- 6 Objects/Frames.- 7 Constraints.- 8 Probabilistic Reasoning.- 9 Non-Monotonic Reasoning.- 10 Temporal Reasoning.- III Problem Classes and Problem-Solving Methods.- 11 Previous Approaches to Problem Classification.- 12 Principles of Problem-Solving Methods.- Classification.- 13 Survey of the Problem-Solving Type Classification.- 14 Simple Classification.- 15 Heuristic Classification.- 16 Heuristic Classification: Additional Mechanisms.- 17 Set-Covering Classification.- 18 Functional Classification.- 19 Statistical Classification.- 20 Case-Comparing Classification.- V Construction.- 21 Review of the Problem-Solving Type Construction.- 22 Skeletal Construction.- 23 Propose and Revise.- 24 Propose and Exchange.- 25 Least-Commitment Strategy.- 26 Model-Based Planning.- 27 Case-Comparing Construction.- 28 Partial Integration of Construction Methods.- VI Simulation.- 29 Review of the Problem-Solving Type Simulation.- 30 Single-Phase Simulation.- 31 Numerical Multiple-Phase Simulation.- 32 Qualitative Multiple-Phase Simulation.- VII Integration of Problem-Solving Methods.- 33 Basic Ideas for the Integration of Problem-Solving Methods.- 34 Integration of Classification Methods.- 35 Aspects of the Overall Integration.- Appendix: Survey of Knowledge Representation Formalisms.- References.- System Index.
Bibliographische Angaben
- Autor: Frank Puppe
- 2012, Softcover reprint of the original 1st ed. 1993, XII, 352 Seiten, 129 Abbildungen, Maße: 15,5 x 23,5 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3642779735
- ISBN-13: 9783642779732
Sprache:
Englisch
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