Decision Making under Various Types of Uncertainty
Applied optimizationPublished 1 January 2000
Ronald R. Yager
Citations20
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TL;DR
It is shown how this method can be applied whatever the uncertainty representation used to model the information about the state of nature: probability distribution, fuzzy set, possibility distribution, a Dempster--Shafer belief structure, or a fuzzy Dempster--Shafer structure.
Abstract
We focus on the problem of decision making in the face of uncertainty The issue of the representation of uncertain information is considered and a number of different frameworks are described: possibilistic, probabilistic, belief structures and graded possibilistic. We suggest methodologies for decision making in these different environments. The importance of decision attitude in the construction of decision functions is strongly emphasized.
Keywords
Computer ScienceDecision Sciences
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