Architecture of Systems Problem Solving

One criterion for classifying books is whether they are written for a single pur pose or for multiple purposes. This book belongs to the category of multipurpose books, but one of its roles is predominant-it is primarily a textbook. As such, it can be used for a variety ofcourses at the first-year graduate or upper-division undergraduate level. A common characteristic of these courses is that they cover fundamental systems concepts, major categories of systems problems, and some selected methods for dealing with these problems at a rather general level. A unique feature of the book is that the concepts, problems, and methods are introduced in the context of an architectural formulation of an expert system referred to as the general systems problem solver or aSPS-whose aim is to provide users ofall kinds with computer-based systems knowledge and methodo logy. Theasps architecture,which is developed throughout the book, facilitates a framework that is conducive to acoherent, comprehensive, and pragmaticcoverage ofsystems fundamentals-concepts, problems, and methods. A course that covers systems fundamentals is now offered not only in sys tems science, information science, or systems engineering programs, but in many programs in other disciplines as well. Although the level ofcoverage for systems science or engineering students is surely different from that used for students in other disciplines, this book is designed to serve both of these needs.

Presents and deconstructs the fundamentals of an expert system and many associated examples Structures as an interdisciplinary that meets the needs of both systems science and engineering students Provides students with a broad base and promotes more in-depth study of the topic Researchers and practitioners benefit from discussion of tools and underdeveloped areas of research Valuable reference text for designers of expert systems

Autorentext
George J. Klir is currently Distinguished Professor of Systems Science at Binghamton University, SUNY. Since he immigrating to the U.S. in 1966, he has held positions at UCLA, Fairleigh Dickinson University, and Binghamton University. He is a Life Fellow of IEEE, IFSA, and the Netherlands Institute for Advanced Studies. He has served as president of SGSR, IFSR, NAFIPS, and IFSA.

Klappentext

This is the definitive text for one of the major schools of thought in systems science. It presents both a comprehensive framework for characterizing all forms of systems problems, and a set of specific methodologies for some key problems. These methodologies are based on a combination of classical and fuzzy set theories, probability and possibility theories, graph and hypergraph theories, and information theory, among others. The hardcopy text contains a revised, updated and condensed version of the first edition, explanatory material drawn from many years of class presentations and lectures, exercises, and fully worked out examples showing both the framework and methodology in operation on actual real-world problems. Fully operational software is made available on an associated website. The material is suitable for upper-level undergraduates and first-year graduate students with a modest background in discrete math, probability and statistics.

Inhalt
1 Introduction.- 1.1 Systems Science.- 1.2 Systems Problem Solving.- 1.3 Hierarchy of Epistemological Levels of Systems.- 1.4 The Role of Mathematics.- 1.5 The Role of Computer Technology.- 1.6 Architecture of Systems Problem Solving.- 2 Source and Data Systems.- 2.1 Objects and Object Systems.- 2.2 Variables and Supports.- 2.3 Methodological Distinctions.- 2.4 Discrete versus Continuous.- 2.5 Image Systems and Source Systems.- 2.6 Data Systems.- 3 Generative Systems.- 3.1 Empirical Investigation.- 3.2 Behavior Systems.- 3.3 Methodological Distinctions.- 3.4 From Data Systems to Behavior Systems.- 3.5 Measures of Uncertainty.- 3.6 Search for Admissible Behavior Systems.- 3.7 State-Transition Systems.- 3.8 Generative Systems.- 3.9 Simplification of Generative Systems.- 3.10 Systems Inquiry and Systems Design.- 4 Structure Systems.- 4.1 Wholes and Parts.- 4.2 Systems, Subsystems, Supersystems.- 4.3 Structure Source Systems and Structure Data Systems.- 4.4 Structure Behavior Systems.- 4.5 Problems of Systems Design.- 4.6 Identification Problem.- 4.7 Reconstruction Problem.- 4.8 Reconstructability Analysis.- 4.9 Simulation Experiments.- 4.10 Inductive Reasoning.- 4.11 Inconsistent Structure Systems.- 5 Metasystems.- 5.1 Change versus Invariance.- 5.2 Primary and Secondary Systems Traits.- 5.3 Metasystems.- 5.4 Metasystems versus Structure Systems.- 5.5 Multilevel Metasystems.- 5.6 Identification of Change.- 6 GSPS: Architecture, Use, Evolution.- 6.1 Epistemological Hierarchy of Systems : Formal Definition.- 6.2 Methodological Distinctions: A Summary.- 6.3 Problem Requirements.- 6.4 Systems Problems.- 6.5 GSPS Conceptual Framework: Formal Definition.- 6.6 Overview of GSPS Architecture.- 6.7 GSPS Use: Some Case Studies.- 6.8 GSPS Evolution.- Author Index.