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A two-steps algorithm for min-based possibilistic causal networks. (English) Zbl 1001.68532
Benferhat, Salem (ed.) et al., Symbolic and quantitative approaches to reasoning with uncertainty. 6th European conference, ECSQARU 2001, Toulouse, France, September 19-21, 2001. Proceedings. Berlin: Springer. Lect. Notes Comput. Sci. 2143, 266-277 (2001).
Summary: In possibility theory, there are two kinds of possibilistic causal networks depending if the possibilistic conditioning is based on the minimum or the product operator. Product-based possibilistic networks share the same practical and theoretical features as Bayesian networks. In this paper, we focus on min-based causal networks and propose a propagation algorithm for such networks. The basic idea is first to transform the initial network only into a moral graph. Then, two different procedures, called stabilization and checking consistency, are applied to compute the possibility degree of any variable of interest given some evidence.
For the entire collection see [Zbl 0971.00035].

MSC:
68T37 Reasoning under uncertainty in the context of artificial intelligence
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