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Problem solving is the very area of artificial intelligence (AI) which, probably, will never result in a complete set of formalized theories, in a pragmatic philosophy, or in a "universal" applied discipline. Studying questions concerning this area encompasses different concepts, models and theories. This volume of the series looks at classifying problems, interpreting them, and the methods of solving them. The final chapter covers future concepts such as universal problem solving approach restoration, weak methods becoming strong, the role of formal logic in future developments, human factors and other paradigms. Different groups of readers such as mathematicians, specialists in computer sciences, and programmers should find this title of interest. Post-graduates and the students specializing in AI and applied mathematics should also find the work useful.
Preface
Introduction
Problem classification. Introduction to the solving methods
Elements of problem solving theory: Application of cutting strategies
Solving discrete optimization problems on the basis of ψ-transform method
Weak methods and heuristic reasoning
Logic-based problem solvers: Approaches and new methods
Programming concepts in problem solving
Future concepts: Some philosophical issues
Glossary
Index