Uncertainty in Artificial Intelligence
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Default Reasoning and the Transferable Belief Model
Philippe Smets, Yen-Teh Hsia
Abstract:
Inappropriate use of Dempster?s rule of combination has led some authors to reject the Dempster-Shafer model, arguing that it leads to supposedly unacceptable conclusions when defaults are involved. A most classic example is about the penguin Tweety. This paper will successively present: the origin of the miss-management of the Tweety example; two types of default; the correct solution for both types based on the transferable belief model (our interpretation of the Dempster-Shafer model (Shafer 1976, Smets 1988)); Except when explicitly stated, all belief functions used in this paper are simple support functions, i.e. belief functions for which only one proposition (the focus) of the frame of discernment receives a positive basic belief mass with the remaining mass being given to the tautology. Each belief function will be described by its focus and the weight of the focus (e.g. m(A)=.9). Computation of the basic belief masses are always performed by vacuously extending each belief function to the product space built from all variables involved, combining them on that space by Dempster?s rule of combination, and projecting the result to the space corresponding to each individual variable.
Keywords: null
Pages: 495-504
PS Link:
PDF Link: /papers/90/p495-smets.pdf
BibTex:
@INPROCEEDINGS{Smets90,
AUTHOR = "Philippe Smets and Yen-Teh Hsia",
TITLE = "Default Reasoning and the Transferable Belief Model",
BOOKTITLE = "Uncertainty in Artificial Intelligence 6 Annual Conference on Uncertainty in Artificial Intelligence (UAI-90)",
PUBLISHER = "Elsevier Science",
ADDRESS = "Amsterdam, NL",
YEAR = "1990",
PAGES = "495--504"
}


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