Enhancing the expressive power of Sugeno integrals for qualitative data analysis

Miguel Couceiro 1 Didier Dubois 2 Henri Prade 2 Agnès Rico 3
1 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : Sugeno integrals are useful for describing families of multiple criteria aggregation functions qualitatively. It is known that Sugeno integrals, as aggregation functions, can be represented by a set of rules. Each rule refers to the same threshold in the conditions about the values of the criteria and in the conclusion pertaining to the value of the integral. However, in the general case we expect rules where several thresholds appear. Some of these rules involving different thresholds can be represented by Sugeno utility functionals where criteria values are rescaled by means of utility functions associated with each criterion. But as shown in this paper, their representation power is quite restrictive. In contrast, we provide evidence to conjecture that the use of disjunctions or conjunctions of Sugeno integrals with utility functions drastically improves the expressive power and that they can capture any aggregation function on a finite scale, understood as piecewise unary aggregation functions.
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Communication dans un congrès
EUSFLAT 2017 - 10th Conference of the European Society for Fuzzy Logic and Technology, Sep 2017, Warsaw, Poland. Springer, Cham, Advances in Intelligent Systems and Computing, 641, pp.534-547, 2017, IWIFSGN 2017, EUSFLAT 2017: Advances in Fuzzy Logic and Technology 2017. 〈http://www.eusflat2017.ibspan.waw.pl/〉. 〈10.1007/978-3-319-66830-7_48〉
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Miguel Couceiro, Didier Dubois, Henri Prade, Agnès Rico. Enhancing the expressive power of Sugeno integrals for qualitative data analysis. EUSFLAT 2017 - 10th Conference of the European Society for Fuzzy Logic and Technology, Sep 2017, Warsaw, Poland. Springer, Cham, Advances in Intelligent Systems and Computing, 641, pp.534-547, 2017, IWIFSGN 2017, EUSFLAT 2017: Advances in Fuzzy Logic and Technology 2017. 〈http://www.eusflat2017.ibspan.waw.pl/〉. 〈10.1007/978-3-319-66830-7_48〉. 〈hal-01668229〉

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