ECSQARU 2011: Symbolic and Quantitative Approaches to Reasoning with Uncertainty pp 287-298 | Cite as
On Consistent Approximations of Belief Functions in the Mass Space
Abstract
In this paper we study the class of consistent belief functions, as counterparts of consistent knowledge bases in classical logic. We prove that such class can be defined univocally no matter our definition of proposition implied by a belief function. As consistency can be desirable in decision making, the problem of mapping an arbitrary belief function to a consistent one arises, and can be posed in a geometric setup. We analyze here all the consistent transformations induced by minimizing L p distances between belief functions, represented by the vectors of their basic probabilities.
Keywords
Simplicial Complex Classical Logic Consistent Approximation Belief Function Paraconsistent LogicPreview
Unable to display preview. Download preview PDF.
References
- 1.Shafer, G.: A Mathematical Theory of Evidence. Princeton University Press, Princeton (1976)MATHGoogle Scholar
- 2.Dempster, A.P.: Upper and lower probabilities induced by a multivariate mapping. Annals of Mathematical Statistics 38, 325–339 (1967)MathSciNetCrossRefMATHGoogle Scholar
- 3.Yager, R.R.: On the dempster-shafer framework and new combination rules. Information Sciences 41, 93–138 (1987)MathSciNetCrossRefMATHGoogle Scholar
- 4.Smets, P.: The degree of belief in a fuzzy event. Inf. Sciences 25, 1–19 (1981)MathSciNetCrossRefMATHGoogle Scholar
- 5.Ramer, A., Klir, G.J.: Measures of discord in the Dempster-Shafer theory. Information Sciences 67(1-2), 35–50 (1993)MathSciNetCrossRefMATHGoogle Scholar
- 6.Liu, W.: Analyzing the degree of conflict among belief functions. Artif. Intell. 170(11), 909–924 (2006)MathSciNetCrossRefMATHGoogle Scholar
- 7.Hunter, A., Liu, W.: Fusion rules for merging uncertain information. Information Fusion 7(1), 97–134 (2006)CrossRefGoogle Scholar
- 8.Lo, K.C.: Agreement and stochastic independence of belief functions. Mathematical Social Sciences 51(1), 1–22 (2006)MathSciNetCrossRefMATHGoogle Scholar
- 9.Paris, J.B., Picado-Muino, D., Rosefield, M.: Information from inconsistent knowledge: A probability logic approach. In: Advances in Soft Computing, vol. 46, pp. 291–307. Springer, Heidelberg (2008)Google Scholar
- 10.Haenni, R.: Towards a unifying theory of logical and probabilistic reasoning. In: Proceedings of ISIPTA 2005, pp. 193–202 (2005)Google Scholar
- 11.Priest, G., Routley, R., Norman, J.: Paraconsistent logic: Essays on the inconsistent. Philosophia Verlag (1989)Google Scholar
- 12.Batens, D., Mortensen, C., Priest, G.: Frontiers of paraconsistent logic. In: Studies in Logic and Computation, vol. 8. Research Studies Press (2000)Google Scholar
- 13.Daniel, M.: On transformations of belief functions to probabilities. International Journal of Intelligent Systems 21(6), 261–282 (2006)CrossRefMATHGoogle Scholar
- 14.Cuzzolin, F.: Two new Bayesian approximations of belief functions based on convex geometry. IEEE Tr. SMC-B 37(4), 993–1008 (2007)Google Scholar
- 15.Dubois, D., Prade, H.: Consonant approximations of belief functions. International Journal of Approximate Reasoning 4, 419–449 (1990)MathSciNetCrossRefMATHGoogle Scholar
- 16.Black, P.: An examination of belief functions and other monotone capacities. PhD dissertation, Department of Statistics, Carnegie Mellon University (1996)Google Scholar
- 17.Cuzzolin, F.: A geometric approach to the theory of evidence. IEEE Transactions on Systems, Man and Cybernetics Part C 38(4), 522–534 (2008)CrossRefGoogle Scholar
- 18.Cuzzolin, F.: Consistent approximations of belief functions. In: Proceedings of ISIPTA 2009, pp. 139–148 (2009)Google Scholar
- 19.Saffiotti, A.: A belief-function logic. In: Universit Libre de Bruxelles, pp. 642–647. MIT Press, CambridgeGoogle Scholar
- 20.Mates, B.: Elementary Logic. Oxford University Press, Oxford (1972)MATHGoogle Scholar
- 21.Cattaneo, M.E.G.V.: Combining belief functions issued from dependent sources. In: ISIPTA, pp. 133–147 (2003)Google Scholar
- 22.de Cooman, G.: Belief models: An order-theoretic investigation. Annals of Mathematics and Artificial Intelligence 45(1-2), 5–34 (2005)MathSciNetCrossRefMATHGoogle Scholar
- 23.Dubrovin, B.A., Novikov, S.P., Fomenko, A.T.: Sovremennaja geometrija. Metody i prilozenija, Nauka, Moscow (1986)Google Scholar
- 24.Cuzzolin, F.: An interpretation of consistent belief functions in terms of simplicial complexes. In: Proc. of ISAIM 2008 (2008)Google Scholar
- 25.Cuzzolin, F.: Geometric conditioning of belief functions. In: Proceedings of BELIEF 2010, Brest, France (2010)Google Scholar