Linguistic Decision Making and Computing with Words

Abstract

Decision making is a common daily life activity for human beings in which, among different choices, they choose the most suitable one for the situation by means of mental and reasoning processes. Decision theory provides a wide range of tools to deal with these problems based on deterministic and probabilistic approaches. However, the uncertainty, vagueness, and imprecision that can be involved in decision problems may not always be modelled in a probabilistic way. In such situations the use of linguistic information is quite natural and common, originating linguistic decision making (LDM). To deal with linguistic descriptors and their inherent vagueness and uncertainty, tools based on fuzzy logic and fuzzy linguistic approaches have risen to facilitate information modelling and enhance the reliability and flexibility of classical decision models. This book is devoted to the use of the 2-tuple linguistic model and its extensions in LDM; this initial chapter tries to clarify the importance of linguistic information in decision making: why is fuzzy linguistic modelling suitable and adequate for complex decision making, and how can LDM problems be solved. The necessity of carrying out computational processes with linguistic information together with the ”Computing with Words” methodology is then reviewed to establish a clear computational basis to operate linguistically in LDM problems. Eventually, a short analysis of different linguistic computational models to show their features and limitations is provided.