Representation of fuzzy measures through probabilities
Fuzzy Sets and Systems
Advances in the Dempster-Shafer theory of evidence
Advances in the Dempster-Shafer theory of evidence
Restored fuzzy measures in expert decision-making
Information Sciences: an International Journal
Classic Works on the Dempster-Shafer Theory of Belief Functions (Studies in Fuzziness and Soft Computing)
On the entropy of fuzzy measures
IEEE Transactions on Fuzzy Systems
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A General model for decision problems is presented in the structure of a body of evidence in the framework of utility theory. Decision maker's preferences valuations on the states of decision systems and possible alternatives (decisions) are presented by utility function. In this case the concept of stochastic dominance is changed by the dominance concept of D-S belief structure, when the utility function is unknown, but there exists some analytical information about it. First, second and higher dominance relations are established. We present theorems about their connections. The maximum principle of Shapley expected utility is explained instead of the maximum principle of Bernoulli expected utility. Because of this, conditional optimization problem is created as nonspecificity measure maximum principle, for which unknown parameters are focal probabilities of a body of evidence.