Uncertainty in Artificial Intelligence
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A Qualitative Linear Utility Theory for Spohn's Theory of Epistemic Beliefs
Phan Giang, Prakash Shenoy
Abstract:
In this paper, we formulate a qualitative "linear" utility theory for lotteries in which uncertainty is expressed qualitatively using a Spohnian disbelief function. We argue that a rational decision maker facing an uncertain decision problem in which the uncertainty is expressed qualitatively should behave so as to maximize "qualitative expected utility." Our axiomatization of the qualitative utility is similar to the axiomatization developed by von Neumann and Morgenstern for probabilistic lotteries. We compare our results with other recent results in qualitative decision making.
Keywords: Spohn's epistemic belief, kappa calculus, qualitative reasoning, utility theory
Pages: 220-229
PS Link:
PDF Link: /papers/00/p220-giang.pdf
BibTex:
@INPROCEEDINGS{Giang00,
AUTHOR = "Phan Giang and Prakash Shenoy",
TITLE = "A Qualitative Linear Utility Theory for Spohn's Theory of Epistemic Beliefs",
BOOKTITLE = "Proceedings of the Sixteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-00)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2000",
PAGES = "220--229"
}


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