Measuring conflict in evidence theory

Mark J. Wierman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Scopus citations

Abstract

The Shannon entropy measures conflict in probabilistic evidence. Evidence Theory also presents information that is inherently conflicting. Uncertainty measures for conflict in Evidence Theory include aggregate uncertainty, dissonance, confusion, discord, granularity and strife. This paper compares and critiques the properties of these measures.

Original languageEnglish
Title of host publicationAnnual Conference of the North American Fuzzy Information Processing Society - NAFIPS
EditorsM.H. Smith, W.A. Gruver, L.O. Hall
Pages1741-1745
Number of pages5
Volume3
StatePublished - 2001
EventJoint 9th IFSA World Congress and 20th NAFIPS International Conference - Vancouver, BC, Canada
Duration: Jul 25 2001Jul 28 2001

Other

OtherJoint 9th IFSA World Congress and 20th NAFIPS International Conference
CountryCanada
CityVancouver, BC
Period7/25/017/28/01

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All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Media Technology

Cite this

Wierman, M. J. (2001). Measuring conflict in evidence theory. In M. H. Smith, W. A. Gruver, & L. O. Hall (Eds.), Annual Conference of the North American Fuzzy Information Processing Society - NAFIPS (Vol. 3, pp. 1741-1745)