Uncertainty in Artificial Intelligence
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A Perspective on Confidence and Its Use in Focusing Attention During Knowledge Acquisition
David Heckerman, Holly Jimison
Abstract:
We present a representation of partial confidence in belief and preference that is consistent with the tenets of decision-theory. The fundamental insight underlying the representation is that if a person is not completely confident in a probability or utility assessment, additional modeling of the assessment may improve decisions to which it is relevant. We show how a traditional decision-analytic approach can be used to balance the benefits of additional modeling with associated costs. The approach can be used during knowledge acquisition to focus the attention of a knowledge engineer or expert on parts of a decision model that deserve additional refinement.
Keywords: Bayesian, Confidence, Decision-Theory
Pages: 123-131
PS Link:
PDF Link: /papers/87/p123-heckerman.pdf
BibTex:
@INPROCEEDINGS{Heckerman87,
AUTHOR = "David Heckerman and Holly Jimison",
TITLE = "A Perspective on Confidence and Its Use in Focusing Attention During Knowledge Acquisition",
BOOKTITLE = "Proceedings of the Third Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-87)",
PUBLISHER = "AUAI Press",
ADDRESS = "Corvallis, Oregon",
YEAR = "1987",
PAGES = "123--131"
}


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