Deriving efficacy from basic uncertain information and uncertain Choquet Integral

Abstract

Basic Uncertain Information (BUI) as a newly introduced concept generalized a wide range of uncertain information. We discuss and compare some methods to derive efficacy from given BUI collection, which is helpful in decision aid. With BUI collection, we also discuss the technique of using Choquet Integral to aggregate those BUI and return closed intervals as final aggregation results, and the whole aggregation is then called Uncertain Choquet Integral. We also discuss Uncertain Choquet Integral with preference, which considers all the information about optimistic/pessimistic preferences of decision makers and in given fuzzy measure. Uncertain Choquet Integral with preference returns real value result instead of closed interval, and it is a type of generalization of Choquet Integral (when all value information are certain) which can be well used in uncertain information environments.