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Belief-based argumentation and golden rule for decision making with soft and hard information

  • Iona College

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

This paper describes a reasoning approach to decision making with uncertain heterogeneous (soft and hard) information of variable reliability based on belief-based argumentation. Arguments are built to support or refute a set of hypotheses about the situation of interest. Beliefs in the arguments are fused and used for decision making. The fusion process is complicated by different models used for representing uncertainty characterizing soft and hard data. The paper addresses this problem by utilizing a unified framework of credibility representation within the Transferable Belief Model. The paper also presents an adaptation of the Golden rule designed for Atanassov type intuitionistic membership grades for decision making based on belief functions. Utilization of the Golden rule representative values allows for dealing with the problem of decision making with not completely ordered intervals created by beliefs and plausibility while taking into account decision maker's subjectivity on the dimension optimism/pessimism.

Original languageEnglish
Title of host publicationFUSION 2016 - 19th International Conference on Information Fusion, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages790-797
Number of pages8
ISBN (Electronic)9780996452748
StatePublished - Aug 1 2016
Event19th International Conference on Information Fusion, FUSION 2016 - Heidelberg, Germany
Duration: Jul 5 2016Jul 8 2016

Publication series

NameFUSION 2016 - 19th International Conference on Information Fusion, Proceedings

Conference

Conference19th International Conference on Information Fusion, FUSION 2016
Country/TerritoryGermany
CityHeidelberg
Period07/5/1607/8/16

Keywords

  • argumentation
  • belief
  • decision makers' subjectivity
  • decision making
  • golden rule
  • hard and soft information

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