Uncertainty in Artificial Intelligence
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Computing Reference Classes
Ronald Loui
For any system with limited statistical knowledge, the combination of evidence and the interpretation of sampling information require the determination of the right reference class (or of an adequate one). The present note (1) discusses the use of reference classes in evidential reasoning, and (2) discusses implementations of Kyburg's rules for reference classes. This paper contributes the first frank discussion of how much of Kyburg's system is needed to be powerful, how much can be computed effectively, and how much is philosophical fat.
Keywords: Reference Classes, Evidential Reasoning
Pages: 273-289
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PDF Link: /papers/86/p273-loui.pdf
AUTHOR = "Ronald Loui ",
TITLE = "Computing Reference Classes",
BOOKTITLE = "Uncertainty in Artificial Intelligence 2 Annual Conference on Uncertainty in Artificial Intelligence (UAI-86)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1986",
PAGES = "273--289"

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