Similarity as a Foundation for Possibility

Research output: Contribution to journalArticlepeer-review

Abstract

A semantics for possibilistic evidential reasoning is presented based on similarity with paradigmatic examples. The acquisition of evidence generates a pseudo-metric on the universe of discourse. It is shown that every possibility distribution can be realized as an embedding in a pseudo-metric space with the possibility values determined by the distance from distinguished elements in that space. Determining support based on similarity captures the fundamental characteristics of possibilistic analysis: optimistic and independent evaluation of the alternatives. The similarity semantics distinguishes possibility from classical approaches to classification and diagnosis problems based on probabilistic techniques.

Original languageAmerican English
JournalNinth IEEE International Conference of Fuzzy Systems
DOIs
StatePublished - Jan 1 2000

Keywords

  • Computer science
  • Heart
  • Histograms
  • Independent component analysis
  • Information analysis
  • Information theory
  • Pattern analysis
  • Pattern recognition
  • Possibility theory
  • Set theory

Disciplines

  • Computer Sciences
  • Engineering
  • Mathematics
  • Physical Sciences and Mathematics

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