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Author Cuzzolin, Fabio
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword L2 Solution ♦ Consistent Transformation ♦ Reasoning Process ♦ Partial Approx-imations ♦ Consistent Trans-formations C ♦ L2 Norm Coincide ♦ Plausibility Element ♦ General Coincide ♦ Consistent Approximation ♦ Consistent Approximation Problem ♦ Clas-sical Lp Norm ♦ Global L1 ♦ Non-contradictory Piece ♦ Arbi-trary Belief Function ♦ Consistent One ♦ Consistent Belief Function ♦ Belief Function
Description Consistent belief functions represent collections of co-herent or non-contradictory pieces of evidence. As most operators used to update or elicit evidence do not preserve consistency, the use of consistent trans-formations cs[·] in a reasoning process to guarantee coherence can be desirable. Such transformations are turn linked to the problem of approximating an arbi-trary belief function with a consistent one. We study here the consistent approximation problem in the case in which distances are measured using clas-sical Lp norms. We show that, for each choice of the element we want them to focus on, the partial approx-imations determined by the L1 and L2 norms coincide, and can be interpreted as classical focused consistent transformations. Global L1 and L2 solutions do not in general coincide, however, nor are they associated with the highest plausibility element.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article
Publisher Date 2009-01-01
Publisher Institution Proceedings of ISIPTA’09