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dc.contributor.authorGiang, Phan H.
dc.contributor.authorShenoy, Prakash P.
dc.date.accessioned2004-12-14T19:49:57Z
dc.date.available2004-12-14T19:49:57Z
dc.date.issued2005-04-16
dc.identifier.citationEuropean Journal of Operational Research, Vol. 162, No. 2, 2005, pp. 450--467.
dc.identifier.issn0377-2217
dc.identifier.urihttp://hdl.handle.net/1808/149
dc.descriptionA preliminary version of this paper appeared as: "A comparison of axiomatic approaches to qualitative decision making using possibility theory. In J. Breese and D. Koller (eds.), Uncertainty in Artificial Intelligence: Proceedings of the Seventeenth Conference (UAI– 2001), 2001, pp. 162–170, Morgan Kaufmann, San Francisco, CA.
dc.description.abstractThis paper proposes a utility theory for decision making under uncertainty that is described by possibility theory. We show that our approach is a natural generalization of the two axiomatic systems that correspond to pessimistic and optimistic decision criteria proposed by Dubois et al. The generalization is achieved by removing axioms that are supposed to reflect attitudes toward uncertainty, namely, pessimism and optimism. In their place we adopt an axiom that imposes an order on a class of canonical lotteries that realize either in the best or in the worst prize. We prove an expected utility theorem for the generalized axiomatic system based on the newly introduced concept of binary utility.
dc.format.extent313433 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.publisherElsevier Science Publishers B. V.
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectDecision theory
dc.subjectUncertainty
dc.subjectPossibility theory
dc.subjectUtility theory
dc.titleTwo Axiomatic Approaches to Decision Making Using Possibility Theory
dc.typeArticle
dc.identifier.orcidhttps://orcid.org/0000-0002-8425-896X
dc.rights.accessrightsopenAccess


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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License
Except where otherwise noted, this item's license is described as: This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License