Architecture of Systems Problem Solving

1. Front Matter

   Pages iii-xv

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2. Introduction

   • George J. Klir, Doug Elias

   Pages 1-25

3. Source and Data Systems

   • George J. Klir, Doug Elias

   Pages 27-71

4. Generative Systems

   • George J. Klir, Doug Elias

   Pages 73-151

5. Structure Systems

   • George J. Klir, Doug Elias

   Pages 153-263

6. Metasystems

   • George J. Klir, Doug Elias

   Pages 265-290

7. GSPS: Architecture, Use, Evolution

   • George J. Klir, Doug Elias

   Pages 291-338

8. Back Matter

   Pages 339-349

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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.

• Problem solving
• Problem-solving
• calculus
• complexity
• computer
• information theory
• mathematics
• probability
• simulation
• statistics
• system
• variable

• State University of New York at Binghamton, Binghamton, USA

  George J. Klir

• Cornell University, Ithaca, USA

  Doug Elias

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