Uncertainty in Artificial Intelligence
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The Probability of a Possibility: Adding Uncertainty to Default Rules
Craig Boutilier
Abstract:
We present a semantics for adding uncertainty to conditional logics for default reasoning and belief revision. We are able to treat conditional sentences as statements of conditional probability, and express rules for revision such as "If A were believed, then B would be believed to degree p." This method of revision extends conditionalization by allowing meaningful revision by sentences whose probability is zero. This is achieved through the use of counterfactual probabilities. Thus, our system accounts for the best properties of qualitative methods of update (in particular, the AGM theory of revision) and probabilistic methods. We also show how our system can be viewed as a unification of probability theory and possibility theory, highlighting their orthogonality and providing a means for expressing the probability of a possibility. We also demonstrate the connection to Lewis's method of imaging.
Keywords:
Pages: 461-468
PS Link:
PDF Link: /papers/93/p461-boutilier.pdf
BibTex:
@INPROCEEDINGS{Boutilier93,
AUTHOR = "Craig Boutilier ",
TITLE = "The Probability of a Possibility: Adding Uncertainty to Default Rules",
BOOKTITLE = "Proceedings of the Ninth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-93)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "1993",
PAGES = "461--468"
}


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