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On the Credal Structure of Consistent Probabilities

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 5293))

Abstract

In this paper we introduce a novel, simpler form of the polytope of inner Bayesian approximations of a belief function, or “consistent probabilities”. We prove that the set of vertices of this polytope is generated by all possible permutations of elements of the domain, mirroring a similar behavior of outer consonant approximations.

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References

  1. Haenni, R., Romeijn, J., Wheeler, G., Williamson, J.: Possible semantics for a common framework of probabilistic logics. In: Huynh, V.N., Nakamori, Y., Ono, H., Lawry, J., Kreinovich, V., Nguyen, H.T. (eds.) UncLog 2008, International Workshop on Interval/Probabilistic Uncertainty and Non-Classical Logics, Ishikawa, Japan. Advances in Soft Computing, vol. 46, pp. 268–279 (2008)

    Google Scholar 

  2. Mercier, D., Denoeux, T., Masson, M.: Refined sensor tuning in the belief function framework using contextual discounting. In: IPMU (2006)

    Google Scholar 

  3. Demotier, S., Schon, W., Denoeux, T.: Risk assessment based on weak information using belief functions: a case study in water treatment. IEEE Transactions on Systems, Man and Cybernetics, Part C 36(3), 382–396 (2006)

    Article  Google Scholar 

  4. Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press, Princeton (1976)

    MATH  Google Scholar 

  5. Dubois, D., Prade, H.: Possibility theory. Plenum Press, New York (1988)

    MATH  Google Scholar 

  6. Smets, P.: Belief functions: the disjunctive rule of combination and the generalized Bayesian theorem. International Journal of Approximate Reasoning 9, 1–35 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  7. Denoeux, T.: A new justification of the unnormalized Dempster’s rule of combination from the Least Commitment Principle. In: Proceedings of FLAIRS 2008, Special Track on Uncertaint Reasoning (2008)

    Google Scholar 

  8. Yager, R.R.: The entailment principle Dempster-Shafer granules. International Journal of Intelligent Systems 1, 247–262 (1986)

    Article  MATH  Google Scholar 

  9. Dubois, D., Prade, H.: A set-theoretic view of belief functions: logical operations and approximations by fuzzy sets. Int. J. of General Systems 12, 193–226 (1986)

    Article  MathSciNet  Google Scholar 

  10. Levi, I.: The enterprise of knowledge: An essay on knowledge, credal probability, and chance. The MIT Press, Cambridge (1980)

    Google Scholar 

  11. Chateauneuf, A., Jaffray, J.Y.: Some characterizations of lower probabilities and other monotone capacities through the use of Möbius inversion. Mathematical Social Sciences 17, 263–283 (1989)

    Article  MATH  MathSciNet  Google Scholar 

  12. Ha, V., Haddawy, P.: Geometric foundations for interval-based probabilities. In: Cohn, A.G., Schubert, L., Shapiro, S.C. (eds.) KR 1998: Principles of Knowledge Representation and Reasoning, pp. 582–593. Morgan Kaufmann, San Francisco (1998)

    Google Scholar 

  13. Smets, P.: The nature of the unnormalized beliefs encountered in the transferable belief model. In: Proceedings of the 8th Annual Conference on Uncertainty in Artificial Intelligence (UAI-92), San Mateo, CA, Morgan Kaufmann (1992) 292–29

    Google Scholar 

  14. Dubois, D., Grabisch, M., Prade, H., Smets, P.: Using the transferable belief model and a qualitative possibility theory approach on an illustrative example: the assessment of the value of a candidate. Intern. J. Intell. Systems (2001)

    Google Scholar 

  15. Snow, P.: The vulnerability of the transferable belief model to dutch books. Artificial Intelligence 105, 345–354 (1998)

    Article  MATH  MathSciNet  Google Scholar 

  16. Smets, P., Kennes, R.: The transferable belief model. AI 66(2), 191–234 (1994)

    MATH  MathSciNet  Google Scholar 

  17. Melkonyan, T., Chambers, R.: Degree of imprecision: Geometric and algebraic approaches. International Journal of Approximate Reasoning (2006)

    Google Scholar 

  18. Cozman, F.G.: Calculation of posterior bounds given convex sets of prior probability measures and likelihood functions. Journal of Computational and Graphical Statistics 8(4), 824–838 (1999)

    Article  MathSciNet  Google Scholar 

  19. Seidenfeld, T., Wasserman, L.: Dilation for convex sets of probabilities. Annals of Statistics 21, 1139–1154 (1993)

    Article  MATH  MathSciNet  Google Scholar 

  20. Seidenfeld, T., Schervish, M., Kadane, J.: Coherent choice functions under uncertainty. In: Proceedings of ISIPTA 2007 (2007)

    Google Scholar 

  21. Baroni, P.: Extending consonant approximations to capacities. In: Proceedings of IPMU, pp. 1127–1134 (2004)

    Google Scholar 

  22. Dubois, D., Prade, H.: Consonant approximations of belief functions. International Journal of Approximate Reasoning 4, 419–449 (1990)

    Article  MATH  MathSciNet  Google Scholar 

  23. Cuzzolin, F.: A geometric approach to the theory of evidence. IEEE Trans. Systems, Man, and Cybernetics C 38(3) (in press, 2008)

    Google Scholar 

  24. Denoeux, T.: Conjunctive and disjunctive combination of belief functions induced by non distinct bodies of evidence. Artificial Intelligence (2007)

    Google Scholar 

  25. Dubois, D., Prade, H., Smets, P.: New semantics for quantitative possibility theory. In: ISIPTA, pp. 152–161 (2001)

    Google Scholar 

  26. Joslyn, C.: Towards an empirical semantics of possibility through maximum uncertainty. In: Lowen, R., Roubens, M. (eds.) Proc. IFSA 1991, pp. 86–89 (1991)

    Google Scholar 

  27. Cuzzolin, F.: The geometry of consonant belief functions: Simplicial complexes of possibility measures. Fuzzy Sets and Systems (under review) (2007)

    Google Scholar 

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Cuzzolin, F. (2008). On the Credal Structure of Consistent Probabilities. In: Hölldobler, S., Lutz, C., Wansing, H. (eds) Logics in Artificial Intelligence. JELIA 2008. Lecture Notes in Computer Science(), vol 5293. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87803-2_12

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  • DOI: https://doi.org/10.1007/978-3-540-87803-2_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-87802-5

  • Online ISBN: 978-3-540-87803-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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