A COMPARISON AMONG SYMBOLIC COMPUTATIONAL MODELS IN LINGUISTIC DECISION MAKING

Decision Making (DM) problems are carried out in many areas of the real world in different situations. We focus on this contribution in DM problems under uncertainty where the information is vague and imprecise. In such a case, the use of linguistic information has provided successful results and implies processes of computing with words (CW). Different computational models have been proposed in the literature to deal with processes of CW. This contribution is aimed to compare different linguistic symbolic computational models applied to Linguistic Decision Making (LDM).