Learning and decision-making in the framework of fuzzy lattices
New learning paradigms in soft computing
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The focus of this work is to provide a procedure for aggregating prioritized belief structures. Motivated by the ideas of nonmonotonic logics an alternative to the normalization step used in Dempster's rule when faced with conflicting belief structures is suggested. We show how this procedure allows us to make inferences in inheritance networks where the knowledge is in the form of a belief structure