Propositional distances and compact preference representation

Published

Journal Article

Distances between possible worlds play an important role in logic-based knowledge representation (especially in belief change, reasoning about action, belief merging and similarity-based reasoning). We show here how they can be used for representing in a compact and intuitive way the preference profile of an agent, following the principle that given a goal G, then the closer a world w to a model of G, the better w. We give an integrated logical framework for preference representation which handles weighted goals and distances to goals in a uniform way. Then we argue that the widely used Hamming distance (which merely counts the number of propositional symbols assigned a different value by two worlds) is generally too rudimentary and too syntax-sensitive to be suitable in real applications; therefore, we propose a new family of distances, based on Choquet integrals, in which the Hamming distance has a position very similar to that of the arithmetic mean in the class of Choquet integrals. © 2003 Elsevier B.V. All rights reserved.

Full Text

Duke Authors

Cited Authors

  • Lafage, C; Lang, J

Published Date

  • February 1, 2005

Published In

Volume / Issue

  • 160 / 3 SPEC. ISS.

Start / End Page

  • 741 - 761

International Standard Serial Number (ISSN)

  • 0377-2217

Digital Object Identifier (DOI)

  • 10.1016/j.ejor.2003.06.037

Citation Source

  • Scopus