Theory and Decision

, Volume 41, Issue 1, pp 59–95 | Cite as

Aggregation of decomposable measures with application to utility theory

  • D. Dubois
  • J. C. Fodor
  • H. Prade
  • M. Roubens
Article

Abstract

This paper investigates the eventwise aggregations of decomposable measures preserving the same decomposable property. These operations are obtained by solving a functional equation closely related to the bisymmetry property. Known results for probability as well as possibility measures can be derived as particular cases of our approach. In addition, the unicity of weighted consensus functions is proved in the Archimedean case. An extension of Von Neumann-Morgenstern utility theory is outlined, where probabilities are changed into decomposable measures.

Key words

Decomposable measures consensus functions measurable utility 

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References

  1. 1.
    Aczél J.: 1966, Lectures on Functional Equations and Applications, Academic Press, New York.Google Scholar
  2. 2.
    C. Alsina: 1985 ‘On a family of connectives for fuzzy sets’, Fuzzy Sets and Systems 16, 231–235.Google Scholar
  3. 3.
    Châteauneuf, A. 1988, Decomposable Measures, Distorted Probabilities and Concave Capacities, CERMSEM, Université de Paris I, France.Google Scholar
  4. 4.
    Choquet, G.: 1953/54 ‘Theory of capacities’, Ann. Inst. Fourier (Grenoble) 5, 131–292.Google Scholar
  5. 5.
    De Finetti, B.: 1937 La prévision: ses lois logiques et ses sources subjectives, Annales Inst. A. Poincaré 7 (1937) 1–68.Google Scholar
  6. 6.
    Dubois, D.: 1986, Belief structure's possibility theory and decomposable measure on finite sets, Computers and AI 5 403–416.Google Scholar
  7. 7.
    Dubois, D. and Prade, H.: 1982, A class of fuzzy measures based on triangular norms-A general framework for the combination of uncertain information, Int. J. of General Systems 8, 43–61.Google Scholar
  8. 8.
    Dubois, D. and Prade, H.: 1986, Weighted minimum and maximum in fuzzy set theory, Inform. Sci. 39, 205–210.Google Scholar
  9. 9.
    Dubois, D. and Prade, H.: 1988, Possibility Theory: An Approach to Computerized Processing of Uncertainty, Plenum Press, New York.Google Scholar
  10. 10.
    Dubois, D. and Prade, H.: 1990, ‘Aggregation of Possibility Measures’, in J. Kacprzyk and M. Fedrizzi (Eds), Multiperson Decision Making Using Fuzzy Sets and Possibility Theory, Kluwer, Dordrecht pp. 55–63.Google Scholar
  11. 11.
    Frank, M.J.: 1979, On the simultaneous associativity of F(x,y) and x + y - F(x, y), Aequationes Mathematicae 19 194–226.Google Scholar
  12. 12.
    Herstein, I.N. and Milnor, J.: 1953, An axiomatic approach to measurable utility, Econometrica 21 291–297.Google Scholar
  13. 13.
    Keeney, R.L.: 1974, Multiplicative utility functions, Operations Research 22 22–34.Google Scholar
  14. 14.
    Kraft, C., Pratt, J.W. and Seidenberg, A.: 1959, Intuitive probability on finite sets, Ann. Math. Stat. 30.Google Scholar
  15. 15.
    Lehrer, K. and Wagner, C.G.: 1981, Rational Consensus in Science and Society (D. Reidel Publ. Co., Boston).Google Scholar
  16. 16.
    Ling, C.H.: 1965, Representation of associative functions, Publ Math. Debrecen 12 189–212.Google Scholar
  17. 17.
    McConway, K.: 1981, Marginalization and linear opinion pools, J. Amer. Statistical Assoc. 76 (1981) 410–414.Google Scholar
  18. 18.
    von Neumann, J. and Morgenstern, O.: 1944, Theory of Games and Economic Behavior (Princeton Univ Press, Princeton, NJ).Google Scholar
  19. 19.
    Pearl, J.: 1993, From qualitative utility to conditional “ought to”, in D. Heckerman, H. Mamdani, Eds., Proc. of the 9th Inter. Conf. on Uncertainty in Artificial Intelligence (Morgan & Kaufmann, San Mateo, CA) 12–20.Google Scholar
  20. 20.
    Savage, L.J.: 1954, The Foundations of Statistics (2d Edition, Dover, New York, 1972).Google Scholar
  21. 21.
    Schmeidler, D.: 1989, Subjective probability and expected utility without additivity, Econometrica 57 571–587.Google Scholar
  22. 22.
    Schweizer, B. and Sklar, A.: 1983, Probabilistic Metric Spaces (North-Holland, Amsterdam).Google Scholar
  23. 23.
    Sugeno, M.: 1974, Theory of Fuzzy Integrals and Its Applications, Doctoral thesis, Tokyo Institute of Technology.Google Scholar
  24. 24.
    Wagner, C.G.: 1989, Consensus for belief functions and related uncertainty measures, Theory and Decision 26 (1989) 295–304.Google Scholar
  25. 25.
    Weber, S.: 1984, ⊥-decomposable measures and integrals for Archimedean t-conorms ⊥, J. Math. Anal. Appl. 101 114–138.Google Scholar
  26. 26.
    Wong, S.K.M., Yao, Y.Y., Bollman P., and Bürger, H.C.: 1991, Axiomatisation of qualitative belief structure, IEEE Trans. on System, Man and Cybernetics 21 726–734.Google Scholar
  27. 27.
    Zadeh, L.A.: 1978, Fuzzy sets as a basis for a theory of possibility, Fuzzy Sets and Systems 1 3–28.Google Scholar

Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • D. Dubois
    • 1
  • J. C. Fodor
    • 1
  • H. Prade
    • 2
  • M. Roubens
    • 3
  1. 1.I.R.I.T - Equipe Intelligence Artificielle et Robotique, Université Paul SabatierToulouse CedexFrance
  2. 2.Department of Computer ScienceEötvös Loránd UniversityBudapestHungary
  3. 3.Institute of Mathematics, University of LiégeLiégeBelgium

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