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On Possibility/Probability Transformations (1993) [17 citations — 5 self]

by Didier Dubois ,  Henri Prade ,  Sandra Sandri
Proceedings of Fourth IFSA Conference
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Abstract:

this paper that the probabilistic representations and the possibilistic ones are not just two equivalent representations of uncertainty. Hence there should be no symmetry between the two mutual conversion procedures. The possibilistic representation is weaker because it explicitly handles imprecision (e.g. incomplete knowledge) and because possibility measures are based on an ordering structure rather than an additive one. Turning a probability measure into a possibility measure may be useful in the presence of other weak sources of information, or when computing with possibilities is simpler than computing with probabilities. Turning a possibility measure into a probability measure might be of interest in the scope of decision-making (Smets, 1990). The next section suggests that the transformations should be guided by two different information principles : the principle of insufficient reason from possibility to probability, and the principle of maximum specificity from probability to possibility. The first principle aims at finding a probability measure which preserves the uncertainty of choice between outcomes, while the second principle aims at finding the most informative possibility distribution, under the constraints dictated by the possibility/probability consistency principle. The paper then proposes two transformations that obey these principles. In the discrete case they are already known. But here, results in the continuous case are given. It is pointed out that these transformations are not related to each other, and the converse transformations are shown to be inadequate. In the last section we discuss the relationship between our approach and other works pertaining to the same topic. Some lines of research are considered.

Citations

321 Fuzzy sets and systems, theory and Applications – Dubois, Prade - 1980
217 Possibility theory : An approach to computerized processing of uncertainty – Dubois, Prade - 1986
40 Constructing the pignistic probability function in a context of uncertainty,” in Uncertainty in – Smets - 1990
34 On Several Representations of an Uncertain Body of Evidence – Dubois, Prade - 1982
18 Uncertainty Models for Knowledge-based Systems – Goodman - 1985
17 Consonant Approximations of Belief Functions – DUBOIS - 1990
13 Unfair coins and necessity measures: towards a possibilistic interpretation of histograms – Dubois, Prade - 1983
11 On the concept of possibility-probability consistency – Delgado, Moral - 1987
11 A principle of uncertainty and information invariance – Klir - 1990
9 Constructing membership functions using statistical data – Civanlar, Trussel - 1986
6 From the Fuzzy Statistics to the Falling Random Subsets – Wang - 1983
5 Single value simulation of fuzzy variable – Chanas, Nowakowski - 1988
5 Scalar evaluations of fuzzy sets: overview and applications – Dubois, Prade - 1990
5 Uncertainty in the Dempster-Shafer theory: A critical reexamination – Klir, Ramer - 1990
4 A mathematical analysis of information-preserving transformations between probabilistic and possibilistic formulations of uncertainty – Geer, Klir - 1992
2 Transforming fuzzy measures – Lamata, Moral, et al. - 1990
2 Construction of a probability distribution from a fuzzy information – Moral - 1986
1 Maximum entropy estimation with inexact information – Leung - 1980
1 La combinaision de l'information incertaine et ses aspects algorithmiques – Sandri - 1991
1 Discussion of Shafer G. "Belief functions and parametric models – Williams - 1982
1 Level sets for membership evaluation of fuzzy subsets – Yager - 1982