Fusion of qualitative information using imprecise 2 -tuple labels

In this chapter, Herrera-Mart́ınez’ 2-tuple linguistic representation model is extended for combining imprecise qualitative information using fusion rules drawn from Dezert-Smarandache Theory (DSmT) or from Dempster-Shafer Theory (DST) frameworks. The proposed approach preserves the precision and the efficiency of the combination of linguistic information. Some basic operators on imprecise 2-tuple labels are presented. We also give simple examples to show how precise and imprecise qualitative information can be combined for reasoning under uncertainty. It is concluded that DSmT can deal efficiently with both precise and imprecise quantitative and qualitative beliefs, which extends the scope of this theory. Acknowledgments: This work was supported by the National Natural Science Foundation of China (No. 60804063).