Measures of assurance and opportunity in modeling uncertain information

  • Authors:
  • Ronald R. Yager

  • Affiliations:
  • Machine Intelligence Institute, Iona College, New Rochelle, NY 10801

  • Venue:
  • International Journal of Intelligent Systems
  • Year:
  • 2012

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Abstract

Our focus is on the representation of uncertain information using set measures. We first discuss the basic properties of monotonic set measures. We then discuss the appropriateness of their use in modeling uncertain information. We look at some notable types of measures of uncertain information and investigate in considerable detail cardinality-based measures. We look at the Sugeno measure and provide a formulation of the underlying cardinality-based measures. We then look at quasi-additive uncertainty measures. We discuss the entropy and attitudinal character of an uncertainty measure. Finally, we introduce the ideas of the assurance and opportunity of the occurrence of an outcome. © 2012 Wiley Periodicals, Inc. (Technical Report #MII-3106R.)