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The Role of Uncertainty in Systems Modeling

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Book cover Discrete Event Modeling and Simulation Technologies

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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.

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Authors
  1. G. J. Klir
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Editors and Affiliations

  1. Electrical and Computer Engineering, University of Arizona, P.O. Box 210104, Tucson, AZ, 85721-0104, USA

    Hessam S. Sarjoughian

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© 2001 Springer Science+Business Media New York

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Klir, G.J. (2001). The Role of Uncertainty in Systems Modeling. In: Sarjoughian, H.S., Cellier, F.E. (eds) Discrete Event Modeling and Simulation Technologies. Springer, New York, NY. https://doi.org/10.1007/978-1-4757-3554-3_4

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  • DOI: https://doi.org/10.1007/978-1-4757-3554-3_4

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4419-2868-9

  • Online ISBN: 978-1-4757-3554-3

  • eBook Packages: Springer Book Archive

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