Enabling local computation for partially ordered preferences

  • Hélène Fargier
  • , Emma Rollon
  • , Nic Wilson

Research output: Contribution to journalArticlepeer-review

Abstract

Many computational problems linked to uncertainty and preference management can be expressed in terms of computing the marginal(s) of a combination of a collection of valuation functions. Shenoy and Shafer showed how such a computation can be performed using a local computation scheme. A major strength of this work is that it is based on an algebraic description: what is proved is the correctness of the local computation algorithm under a few axioms on the algebraic structure. The instantiations of the framework in practice make use of totally ordered scales. The present paper focuses on the use of partially ordered scales and examines how such scales can be cast in the Shafer-Shenoy framework and thus benefit from local computation algorithms. It also provides several examples of such scales, thus showing that each of the algebraic structures explored here is of interest.

Original languageEnglish
Pages (from-to)516-539
Number of pages24
JournalConstraints
Volume15
Issue number4
DOIs
Publication statusPublished - Oct 2010

Keywords

  • Dynamic programming
  • Local computation
  • Soft constraints
  • Valuation networks/algebra

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