Plausible reasoning from spatial observations

Authors:
Jérôme Lang;Philippe Muller
Affiliations:
IRIT, Université Paul Sabatier, Toulouse, France;IRIT, Université Paul Sabatier, Toulouse, France
Venue:
UAI'01 Proceedings of the Seventeenth conference on Uncertainty in artificial intelligence
Year:
2001

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Abstract

This article deals with plausible reasoning from incomplete knowledge about large-scale spatial properties. The available information, consisting of a set of pointwise observations, is extrapolated to neighbour points. We use 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 are aggregated using a variant of Dempster's rule of combination taking into account the relative dependence between observations.