Application of linear utility theory to belief functions
Proceedings of the 2nd International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems on Uncertainty and intelligent systems
A valuation-based language for expert systems
International Journal of Approximate Reasoning
Decision analysis using belief functions
International Journal of Approximate Reasoning
A fusion algorithm for solving Bayesian decision problems
Proceedings of the seventh conference (1991) on Uncertainty in artificial intelligence
Valuation-based systems: a framework for managing uncertainty in expert systems
Fuzzy logic for the management of uncertainty
Constructing the Pignistic Probability Function in a Context of Uncertainty
UAI '89 Proceedings of the Fifth Annual Conference on Uncertainty in Artificial Intelligence
Valuation-based systems for discrete optimisation
UAI '90 Proceedings of the Sixth Annual Conference on Uncertainty in Artificial Intelligence
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Valuation-based system (VBS) provides a general framework for representing knowledge and drawing inferences under uncertainty. Recent studies have shown that the semantics of VBS can represent and solve Bayesian decision problems (Shenoy, 1991a). The purpose of this paper is to propose a decision calculus for Dempster-Shafer (D-S) theory in the framework of VBS. The proposed calculus uses a weighting factor whose role is similar to the probabilistic interpretation of an assumption that disambiguates decision problems represented with belief functions (Start 1990). It will be shown that with the presented calculus, if the decision problems are represented in the valuation network properly, we can solve the problems by using fusion algorithm (Shenoy 1991a). It will also be shown the presented decision calculus can be reduced to the calculus for Bayesian probability theory when probabilities, instead of belief functions, are given.