Uncertainty in Artificial Intelligence
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A new axiomatization for likelihood gambles
Phan Giang
Abstract:
This paper studies a new and more general axiomatization than one presented previously for preference on likelihood gambles. Likelihood gambles describe actions in a situation where a decision maker knows multiple probabilistic models and a random sample generated from one of those models but does not know prior probability of models. This new axiom system is inspired by Jensen's axiomatization of probabilistic gambles. Our approach provides a new perspective to the role of data in decision making under ambiguity. It avoids one of the most controversial issue of Bayesian methodology namely the assumption of prior probability.
Keywords:
Pages: 192-199
PS Link:
PDF Link: /papers/06/p192-giang.pdf
BibTex:
@INPROCEEDINGS{Giang06,
AUTHOR = "Phan Giang ",
TITLE = "A new axiomatization for likelihood gambles",
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 = "192--199"
}


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