Uncertainty in Artificial Intelligence
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Conditional Utility, Utility Independence, and Utility Networks
Yoav Shoham
Abstract:
We introduce a new interpretation of two related notions - conditional utility and utility independence. Unlike the traditional interpretation, the new interpretation renders the notions the direct analogues of their probabilistic counterparts. To capture these notions formally, we appeal to the notion of utility distribution, introduced in previous paper. We show that utility distributions, which have a structure that is identical to that of probability distributions, can be viewed as a special case of an additive multiattribute utility functions, and show how this special case permits us to capture the novel senses of conditional utility and utility independence. Finally, we present the notion of utility networks, which do for utilities what Bayesian networks do for probabilities. Specifically, utility networks exploit the new interpretation of conditional utility and utility independence to compactly represent a utility distribution.
Keywords: Utility functions, utility distributions, utility networks, bi-distributions, bi-net
Pages: 429-436
PS Link:
PDF Link: /papers/97/p429-shoham.pdf
BibTex:
@INPROCEEDINGS{Shoham97,
AUTHOR = "Yoav Shoham ",
TITLE = "Conditional Utility, Utility Independence, and Utility Networks",
BOOKTITLE = "Proceedings of the Thirteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-97)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1997",
PAGES = "429--436"
}


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