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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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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