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Systematic Introduction to Expert Systems: Knowledge Representations and Problem-Solving Methods

โœ Scribed by Frank Puppe (auth.)


Publisher
Springer-Verlag Berlin Heidelberg
Year
1993
Tongue
English
Leaves
352
Edition
1
Category
Library

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โœฆ Synopsis


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.

โœฆ Table of Contents


Front Matter....Pages I-XII
Front Matter....Pages 1-1
Characterization and History of Expert Systems....Pages 3-8
Programming Languages and Expert System Tools....Pages 9-16
Use and Usability of Expert Systems....Pages 17-25
Front Matter....Pages 27-27
Logic....Pages 29-34
Rules....Pages 35-42
Objects/Frames....Pages 43-50
Constraints....Pages 51-56
Probabilistic Reasoning....Pages 57-70
Non-Monotonic Reasoning....Pages 71-78
Temporal Reasoning....Pages 79-86
Front Matter....Pages 87-87
Previous Approaches to Problem Classification....Pages 89-100
Principles of Problem-Solving Methods....Pages 101-111
Front Matter....Pages 113-113
Survey of the Problem-Solving Type Classification....Pages 115-127
Simple Classification....Pages 128-130
Heuristic Classification....Pages 131-148
Heuristic Classification: Additional Mechanisms....Pages 149-155
Set-Covering Classification....Pages 156-169
Functional Classification....Pages 170-182
Statistical Classification....Pages 183-190
Case-Comparing Classification....Pages 191-204
Front Matter....Pages 205-205
Review of the Problem-Solving Type Construction....Pages 207-215
Skeletal Construction....Pages 216-222
Propose and Revise....Pages 223-228
Propose and Exchange....Pages 229-239
Least-Commitment Strategy....Pages 240-248
Model-Based Planning....Pages 249-252
Case-Comparing Construction....Pages 253-254
Partial Integration of Construction Methods....Pages 255-261
Front Matter....Pages 263-263
Review of the Problem-Solving Type Simulation....Pages 265-268
Single-Phase Simulation....Pages 269-270
Numerical Multiple-Phase Simulation....Pages 271-277
Qualitative Multiple-Phase Simulation....Pages 278-283
Front Matter....Pages 285-285
Basic Ideas for the Integration of Problem-Solving Methods....Pages 287-294
Integration of Classification Methods....Pages 295-313
Aspects of the Overall Integration....Pages 314-321
Back Matter....Pages 322-352

โœฆ Subjects


Artificial Intelligence (incl. Robotics); Programming Languages, Compilers, Interpreters; Business Information Systems


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