Uncertainty in Artificial Intelligence
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Axiomatic Foundations for a Class of Generalized Expected Utility: Algebraic Expected Utility
Paul Weng
Abstract:
Expected Utility: Algebraic Expected Utility In this paper, we provide two axiomatizations of algebraic expected utility, which is a particular generalized expected utility, in a von Neumann-Morgenstern setting, i.e. uncertainty representation is supposed to be given and here to be described by a plausibility measure valued on a semiring, which could be partially ordered. We show that axioms identical to those for expected utility entail that preferences are represented by an algebraic expected utility. This algebraic approach allows many previous propositions (expected utility, binary possibilistic utility,...) to be unified in a same general framework and proves that the obtained utility enjoys the same nice features as expected utility: linearity, dynamic consistency, autoduality of the underlying uncertainty measure, autoduality of the decision criterion and possibility of modeling decision maker's attitude toward uncertainty.
Keywords:
Pages: 520-527
PS Link:
PDF Link: /papers/06/p520-weng.pdf
BibTex:
@INPROCEEDINGS{Weng06,
AUTHOR = "Paul Weng ",
TITLE = "Axiomatic Foundations for a Class of Generalized Expected Utility: Algebraic Expected Utility",
BOOKTITLE = "Proceedings of the Twenty-Second Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-06)",
PUBLISHER = "AUAI Press",
ADDRESS = "Arlington, Virginia",
YEAR = "2006",
PAGES = "520--527"
}


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