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dc.contributor.authorGiang, Phan H.
dc.contributor.authorShenoy, Prakash P.
dc.date.accessioned2004-12-14T21:39:37Z
dc.date.available2004-12-14T21:39:37Z
dc.date.issued2003-08
dc.identifier.citationU. Kjærulff and C. Meek (eds.), Uncertainty in Artificial Intelligence, 2003, pp. 272--280, Morgan Kaufmann, San Francisco, CA
dc.identifier.isbn0-127-05664-5
dc.identifier.urihttp://hdl.handle.net/1808/153
dc.description.abstractThis paper studies decision making for Walley’s partially consonant belief functions (pcb). In a pcb, the set of foci are partitioned. Within each partition, foci are nested. The pcb class includes probability and possibility functions as extreme cases. We adopt an axiomatic system, similar in spirit to von Neumann and Morgenstern’s axioms for preferences leading to the linear utility theory, for a preference relation on pcb lotteries. We prove a representation theorem for this preference relation. Utility for a pcb lottery is a combination of linear utility for probabilistic lottery and binary utility for possibilistic lottery.
dc.format.extent421318 bytes
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.publisherMorgan Kaufmann Publishers
dc.subjectDecision theory
dc.subjectPartially consonant belief functions
dc.subjectUtility theory
dc.subjectAxioms
dc.titleDecision Making with Partially Consonant Belief Functions
dc.typeBook chapter
kusw.oastatusna
dc.identifier.orcidhttps://orcid.org/0000-0002-8425-896X
kusw.oapolicyThis item does not meet KU Open Access policy criteria.
dc.rights.accessrightsopenAccess


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