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Expected Utility Networks in Transferable Belief Model

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Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2206))

Abstract

Traditional Bayesian decision analysis is based on probability theory and utility theory. However, expected utility model can be derived also in the other models proposed to quantify someone’s belief. We shall deal only with the transferable belief model. The purpose of this paper is to introduce a new class of graphical representation to simplify the decision process.

This work has been supported by the grant No. 2/1102/21 of the Scientific Grant Agency of Ministry of Education of Slovak Republik and Slovak Academy of Sciences.

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References

  1. Ben Yaghlane, B., Smets, P., Mellouli, K.: Independence and non-interactivity in the transferable belief model. In: Workshop on conditional independence structures and graphical models. F. Matús and M. Studený (Eds.). Abstract book. Toronto, Canada, (1999) 4–5

    Google Scholar 

  2. Dubois, D. and Prade, H.: Decision Evaluation Methods under Uncertainty and Imprecision. In: Combining Fuzzy Imprecision with Probabilistic Uncertainty in Decision Making. J. Kacprzyk and M. Federizzi (Eds.), Springer, (1987) 48–65

    Google Scholar 

  3. Mura, P. and Shoham, Y.: Expected Utility Networks. In: Proceedings of the 15th Conference on Uncertainty in Artificial Intelligence. K.B. Laskey and H. Prade (Eds.), Morgan Kaufmann Publishers, Inc. San Francisco, (1999)

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  4. Smets, P.: Constructing the Pignistic Probability Function in a Context of Uncertainty. In: Uncertainty in Artificial Intelligence. M. Henrion, R. Shachter, L.N. Kanal and J. Lemmer (Eds.),5 North-Holland, Amsterdam, (1990) 29–40

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  5. Smets, P.: Decision Making in a Context where Uncertainty is Represented by Belief Functions. In:Belief Functions in Business Decisions. Srivastava, R.(Eds.) Physica Verlag. Forthcoming. (2001)

    Google Scholar 

  6. Smets, P. and Kennes, R.: The Transferable Belief Model. Artif. Intell. 66 (1994) 191–234

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© 2001 Springer-Verlag Berlin Heidelberg

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Slobodová, A. (2001). Expected Utility Networks in Transferable Belief Model. In: Reusch, B. (eds) Computational Intelligence. Theory and Applications. Fuzzy Days 2001. Lecture Notes in Computer Science, vol 2206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45493-4_79

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  • DOI: https://doi.org/10.1007/3-540-45493-4_79

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42732-2

  • Online ISBN: 978-3-540-45493-9

  • eBook Packages: Springer Book Archive

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