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2003 | Buch | 2. Auflage

Architecture of Systems Problem Solving

verfasst von: George J. Klir, Doug Elias

Verlag: Springer US

Buchreihe : IFSR International Series in Systems Science and Systems Engineering

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Über dieses Buch

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.

Inhaltsverzeichnis

Frontmatter
Chapter 1. Introduction
Abstract
The evolution of a highly complex hierarchy of disciplinary specializations has been one of the major characteristics of the history of science. The ancient scientist/philosopher such as Aristotle, who was able to comprehend almost all knowledge available in his time, has gradually been replaced by generations of scientists with ever-increasing depth of knowledge and narrowness of interest and competence.
George J. Klir, Doug Elias
Chapter 2. Source and Data Systems
Abstract
As human beings, we are able to distinguish ourselves from our environment. Our immediate awareness of the environment is a result of our perception. We have also the ability to store, process, and utilize information received from the environment, and this, in turn, reinforces our perception. These abilities are fundamental for our survival and well-being. They allow us to make decisions and act appropriately.
George J. Klir, Doug Elias
Chapter 3. Generative Systems
Abstract
There are three prerequisites for every meaningful empirical investigation. First, an object of investigation must be identified; second, a purpose of investigating the object must be known; third, constraints imposed upon the investigation must be assessed.
George J. Klir, Doug Elias
Chapter 4. Structure Systems
Abstract
The determination of a generative system (or a set of admissible generative systems), as discussed in Chapter 3, is only the first theoretical stage in systems inquiries. New challenges arise when higher epistemological types of systems become involved. This chapter is devoted to problems that arise in connection with structure systems.
George J. Klir, Doug Elias
Chapter 5. Metasystems
Abstract
One of the most fundamental human capabilities, perhaps the most fundamental, is the capability of recognizing differences. Its most primitive manifestation is the making of distinctions by human beings, as well depicted by Goguen and Varela [GO1]:
A distinction splits the world into two parts, “that” and “this,” or “environment” and “system,” or “us” and “them,” etc. One of the most fundamental of all human activities is the making of distinctions. Certainly, it is the most fundamental act of system theory, the very act of defining the system presently of interest, of distinguishing it from its environment.
George J. Klir, Doug Elias
Chapter 6. GSPS: Architecture, Use, Evolution
Abstract
Epistemological types of systems that are recognized within the GSPS framework include source systems and their components (object systems, specific and general image systems), data systems, generative systems (behavior systems or ST-systems), structure system of various types and levels, and metasystems of various types and levels. In addition, each of these systems types can be either neutral or directed.
George J. Klir, Doug Elias
Backmatter
Metadaten
Titel
Architecture of Systems Problem Solving
verfasst von
George J. Klir
Doug Elias
Copyright-Jahr
2003
Verlag
Springer US
Electronic ISBN
978-1-4419-9224-6
Print ISBN
978-1-4613-4846-7
DOI
https://doi.org/10.1007/978-1-4419-9224-6