Uncertainty in Artificial Intelligence
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Plausible reasoning from spatial observations
Jerome Lang, Philippe Muller
Abstract:
This article deals with plausible reasoning from incomplete knowledge about large-scale spatial properties. The availableinformation, consisting of a set of pointwise observations,is extrapolated to neighbour points. We make use of belief functions to represent the influence of the knowledge at a given point to another point; the quantitative strength of this influence decreases when the distance between both points increases. These influences arethen aggregated using a variant of Dempster's rule of combination which takes into account the relative dependence between observations.
Keywords:
Pages: 285-292
PS Link:
PDF Link: /papers/01/p285-lang.pdf
BibTex:
@INPROCEEDINGS{Lang01,
AUTHOR = "Jerome Lang and Philippe Muller",
TITLE = "Plausible reasoning from spatial observations",
BOOKTITLE = "Proceedings of the Seventeenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-01)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2001",
PAGES = "285--292"
}


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