Abstract
This paper deals with coherent conditional probability able to manage uncertainty, partial knowledge and conditional independence, overcoming the critical situations presented by the classic independence definition. When a probability is not complete (i.e. it is defined on an arbitrary set of conditional events) the conditional independence statements are not necessarily automatically induced by the values of the assessment, so given a set of independence statements its compatibility with the numerical values (conditional probability) need to be checked. This problem related to the compatibility of independence statements and conditional probability assessment is studied and a procedure for checking the compatibility is proposed.
Explore related subjects
Discover the latest articles, news and stories from top researchers in related subjects.References
Billingsley P (1995) Probability and Measure. Wiley, New York
Bouchon-Meunier B, Coletti G, Marsala C (2002) Independence and possibilistic conditioning. Ann Math Artif Intell 35: 107–124
Capotorti A, Vantaggi B (2002) Locally strong coherence in inferential processes. Ann Math Artif Intell 35: 125–149
Capotorti A, Vantaggi B (2003) Locally strong coherence and inference with lower-upper probabilities. Soft Comput 7(5): 280–287
Coletti G (1994) Coherent numerical and ordinal probabilistic assessments. IEEE Trans Syst Man Cybern 24(12): 1747–1754
Coletti G, Scozzafava R (1996) Characterization of coherent conditional probabilities as a tool for their assessment and extension. Int J Uncertainty Fuzziness Knowl-Based System, 4(2): 103–127
Coletti G, Scozzafava R (1997) Exploiting Zero Probabilities. In: Proceedings of EUFIT’97, Aachen, Germany, ELITE Foundation 1499–1503
Coletti G, Scozzafava R (1998) Null events and stochastical independence. Kibernetika, 34(1): 69–78
Coletti G, Scozzafava R (2000) Zero probabilities in stochastic independence, Information, Uncertainty, Fusion Bouchon-Meunier B, Yager RR, Zadeh LA (Eds.) Kluwer, Dordrecht 185–196 (Selected papers from IPMU ‘98).
Coletti G, Scozzafava R (1999) Conditioning and inference in intelligent systems. Soft Computing 3: 118–130
Coletti G, Scozzafava R (2000) The Role of Coherence in Eliciting and Handling ‘‘Imprecise’’ Probabilities and its Application to Medical Diagnosis. Inf Sci 130: 41–65
Coletti G, Scozzafava R, Vantaggi B (2001) Probabilistic Reasoning as a General Unfying Tool. Lect Notes Comput Sci Benferhat S, Besnard P (Eds.) Vol. LNAI 2143, pp 120–131, Springer-Verlag, Berlin
Coletti G, Scozzafava R (2001) From conditional events to conditional measures: a new axiomatic approach. Ann Math Artif Intell 32: 373–392
Coletti G, Scozzafava R (2001) Stochastic independence in a coherent setting. Ann Math Artif Intell 35: 151–176
Coletti G, Scozzafava R (2002) Probabilistic logic in a coherent setting. Trends in logic n. 15, Kluwer Dordrecht
Coletti G, Scozzafava R (2003) Toward a general theory of conditional beliefs. In: Proceedings of 6th Workshop on Uncertainty Processing, Hejnice, Czeck Republic, 65–76 (An extended version has been submitted in International Journal of Intelligent Systems)
de Dombal FT, Gremy F (1976) (Eds.) Decision Making and Medical Care. North Holland
de Finetti B (1949) Sull’impostazione assiomatica del calcolo delle probabilitá. Annali dell’Universitá di Trieste 19: 3–55 (Eng. transl.: Ch. 5 in Probability, Induction, Statistics, London: Wiley, 1972)
Dempster AP (1967) Upper and lower probabilities induced by a multivalued mapping. Ann Math 38: 325–339
Dubins LE (1975) Finitely additive conditional probabilities, conglomerability and disintegration. Ann Probab 3: 89–99
Dubois D, Prade H (1994) Conditional objects as nonmonotonic consequence relationships. IEEE Trans Syst Man Cybern 24(12): 1724–1740
Hill JR (1993) Comment on ‘‘Graphical models”. Stat Sci 8: 258–261
Holzer S (1985) On coherence and conditional prevision. Bull. Unione Matematica Italiana, Analisi funzionale e applicazioni 6(4): 441–460
Jirousek R (1991) Solution of the marginal problem and decomposable distributions. Kybernetika 27: 403–412
Nguyen HT, Walker EA (1997) A first course in fuzzy logic. CRC Press
Krauss PH (1968) Representation of conditional probability measures on Boolean algebras. Acta Math. Acad Scient Hungar 19: 229–241
Regazzini E (1985) Finitely additive conditional probabilities. Rend Sem Mat Fis Milano 55: 69–89
Rényi A (1956) On conditional probability spaces generated by a dimensionally ordered set of measures. Theor Probab Appl 1: 61–71
Shafer G (1976) A mathematical theory of evidence. Princeton University Press, New York
Scozzafava R (2000) The role of probability in statistical physics. Transport Theor Stat Phys 29(1–2): 107–123
Studeny M (1995) Marginal problem in different calculi of AI. Lecture Notes in Computer Science 945, Springer-Verlag, Berlin - Heidelberg pp 348–359
Vantaggi B (2001) Conditional independence in a finite coherent setting. Ann Math Artif Intell 32: 287–314
Vantaggi B (2002) The L-separation criterion for description of cs-independence models. Int J Approximate Reasoning 29: 291–316
Vantaggi B (2003) Graphical Representation of Asymmetric Graphoid Structures. Proceeding del ‘‘3rd International Symposium on Imprecise Probabilities and their Applications’’ (Eds. Bernard, Seidenfels, Zaffalon), Carlenton Scientific pp 562–576
Vantaggi B (2003) Conditional Independence Structures and Graphical Models. Int J Uncertainty Fuzziness Knowl-based Syst 11(5): 545–571
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Vantaggi, B. The role of coherence for handling probabilistic evaluations and independence. Soft Comput 9, 617–628 (2005). https://doi.org/10.1007/s00500-004-0407-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00500-004-0407-2