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Group Preference Modelling in SMAA Using Belief Functions

Risto Lahdelma, Tommi Tervonen, Pekka Salminen, José Figueira, Group Preference Modelling in SMAA Using Belief Functions. In: Proceedings of the 23rd IASTED International Multi-Conference on Artificial Intelligence and Applications, 381-386, 2005.

Abstract:

Stochastic Multicriteria Acceptability Analysis (SMAA) is
a family of methods to aid decision makers (DMs) in discrete
decision making problems. SMAA methods are capable
of handling preference information of various types.
The imperfect knowledge about the preferences of multiple
DMs can for example be represented by a joint probability
distribution for criteria weights (scale factors).
<br>
Dempster-Shafer theory of evidence (DST) is a generalization
of the classic Bayesian probability theory, that
allows modelling of ignorance by using belief functions. In
this paper we show how the preferences of multiple DMs
can be modelled and combined using DST, and how this
information can then be encoded as interval constraints for
sets of weights in SMAA.

BibTeX entry:

@INPROCEEDINGS{inpLaTeSaFi05a,
  title = {Group Preference Modelling in SMAA Using Belief Functions},
  booktitle = {Proceedings of the 23rd IASTED International Multi-Conference on Artificial Intelligence and Applications},
  author = {Lahdelma, Risto and Tervonen, Tommi and Salminen, Pekka and Figueira, José},
  pages = {381-386},
  year = {2005},
  keywords = {Stochastic Multicriteria Acceptability Analysis, Preference Modelling, Multicriteria Decision Aiding, Group Decision Making},
}

Belongs to TUCS Research Unit(s): Algorithmics and Computational Intelligence Group (ACI)

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