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The Role of Uncertainty in Systems Modeling

  • G. J. Klir
Chapter

Abstract

A personal account of the emergence and development of generalized information theory (GIT) in the context of data-driven (inductive) systems modeling. In GIT, information is defined in terms of relevant uncertainty reduction. Main results regarding measures of uncertainty and uncertainty-based information in Dempster-Shafer theory of evidence and in generalized possibility theory are overviewed, and their role in three basic uncertainty principles is discussed: the principles of maximum uncertainty, minimum uncertainty, and uncertainty invariance. Finally, some open problems and undeveloped areas in GIT are examined.

Keywords

Shannon Entropy Uncertainty Theory Possibility Theory Focal Element Basic Probability Assignment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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© Springer Science+Business Media New York 2001

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  • G. J. Klir

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