Uncertainty in Artificial Intelligence
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Decision Making with Partially Consonant Belief Functions
Phan Giang, Prakash Shenoy
Abstract:
This paper studies decision making for Walley's partially consonant belief functions (pcb ). In a pcb, the set of foci are partitioned. Within each partition, the foci are nested. The pcb class includes probability functions and possibility functions as extreme cases. Unlike earlier proposals for a decision theory with belief functions, we employ an axiomatic approach. We adopt an axiom system similar in spirit to von Neumann - Morgenstern's linear utility theory for a preference relation on pcb lotteries. We prove a representation theorem for this relation. Utility for a pcb lottery is a combination of linear utility for probabilistic lottery and binary utility for possibilistic lottery.
Keywords: decision making, belief functions
Pages: 272-280
PS Link:
PDF Link: /papers/03/p272-giang.pdf
BibTex:
@INPROCEEDINGS{Giang03,
AUTHOR = "Phan Giang and Prakash Shenoy",
TITLE = "Decision Making with Partially Consonant Belief Functions",
BOOKTITLE = "Proceedings of the Nineteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-03)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2003",
PAGES = "272--280"
}


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