Advances in the Egalitarist Approach to Decision-Making in a Fuzzy Environment

  • Didier Dubois
  • Henri Prade
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 73)


This paper proposes a unified approach to decision-making in a fuzzy environment, based on the original idea of Bellman and Zadeh, encompassing fuzzy optimization, fuzzy relational calculus and possibility theory. This approach subsumes the paradigm of constraint-directed reasoning in Artificial Intelligence and allows for flexible or prioritized constraints. More generally the use of Sugeno integral enables to model generalized forms of prioritizing and the inclusion of fuzzy quantifiers in the conjunctive aggregation of local satisfaction levels. It is shown that the egalitarist (maximin) criterion of Bellman and Zadeh must be refined in order to make it Pareto-efficient. Two such refinements called “discrimin” and “leximin” are described. Some results about how to compute such optimal solutions are provided. The proposed framework enables uncertainty to be handled as well. Decision theory is reexamined in the light of possibility theory and Sugeno integral. Older fuzzy pattern matching evaluations turn out to be possibilistic counterparts of expected utility, suitable for a sound modelling of non-repeated decision under uncertainty.


Possibility Distribution Possibility Theory Fuzzy Constraint Fuzzy Domain Flexible Constraint 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Didier Dubois
    • 1
  • Henri Prade
    • 1
  1. 1.Institut de Recherche en Informatique de Toulouse (IRIT) — CNRSUniversité Paul SabatierToulouse Cedex 4France

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