Probability-generated aggregators

Evgeny Kagan, Alexander Rybalov, Hava Siegelmann, Ronald Yager

Research output: Contribution to journalArticlepeer-review

Abstract

The paper addresses a relation between logical reasoning and probability and presents probability-generated aggregators. The obtained aggregators implement probability distributions for specification of generator functions; as it was proven in the paper, such implementation is always possible. In the paper, the relation between neutral element of the probabilistic uninorm and parameters of the underlying probability distribution is demonstrated, and a method for specification of the probabilistic uninorm, and thus - of the probability distribution using t-norm and t-conorm - is constructed. In addition, the obtained probabilistic uninorm and probabilistic absorbing norm or nullnorm are briefly considered as algebraic operations on the open unit interval. In is demonstrated, that, in general, the obtained algebra is nondistributive and depends on the distributions, which are used for generating probabilistic uninorm and absorbing norm. The obtained results bridge several gaps between fuzzy and probabilistic logics and provide a basis both for theoretical studies in the field and for practical techniques of digital/analog schemes synthesis and analysis.

Original languageEnglish
Pages (from-to)709-727
Number of pages19
JournalInternational Journal of Intelligent Systems
Volume28
Issue number7
DOIs
StatePublished - Jul 2013

All Science Journal Classification (ASJC) codes

  • Software
  • Theoretical Computer Science
  • Human-Computer Interaction
  • Artificial Intelligence

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