Systematic Introduction to Expert Systems
Knowledge Representations and Problem-Solving Methods
Published on 6. December 2012
XII, 352 pages
978-3-642-77971-8 (ISBN)
Description
At present one of the main obstacles to a broader
application of expert systems is the lack of a theory to
tell us which problem-solving methods areavailable for a
given problem class. Such a theory could lead to significant
progress in the following central aims of the expert system
technique:
- Evaluating the technical feasibility of expert system
projects: This depends on whether there is a suitable
problem-solving method, and if possible a corresponding
tool, for the given problem class.
- Simplifying knowledge acquisition and maintenance: The
problem-solving methods provide direct assistance as
interpretation models in knowledge acquisition. Also, they
make possible the development of problem-specific expert
system tools with graphical knowledge acquisition
components, which can be used even by experts without
programming experience.
- Making use of expert systems as a knowledge medium: The
structured knowledge in expert systems can be used not only
for problem solving but also for knowledge communication and
tutorial purposes.
With such a theory in mind, this book provides a systematic
introduction to expert systems. It describes the basic
knowledge representations and the present situation with
regard tothe identification, realization, and integration
of problem-solving methods for the main problem classes of
expert systems: classification (diagnostics), construction,
and simulation.
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Other editions
Additional editions
Frank Puppe
Systematic Introduction to Expert Systems
Knowledge Representations and Problem-Solving Methods
Book
05/1993
Springer
€85.55
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Content
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.
