XX Spanish Congress on Fuzzy Logic and Technologies

Decision-making is a common activity in various fields of application and research areas (engineering, social sciences, health sciences, information technologies, etc.). The cross-cutting nature of this research area has led to the development of different models, different approaches and perspectives in a wide range of disciplines such as Psychology, Economics, Political Science, Social Choice, Operations Research, Medicine, Artificial Intelligence, Engineering, etc. This session focuses on environments where the objectives, constraints or possible alternatives associated with decision making processes are not precisely known, i.e. decision making processes in uncertain environments. The aim of this special session is to provide an opportunity to discuss and disseminate the most recent theoretical and empirical advances in this field to show the versatility and applicability of these techniques.

Decision Making (DM) is a common activity in various fields of application and research areas (engineering, social sciences, psychology, information technologies, etc.). This wide range of application fields has led to the study of these problems from different approaches and perspectives. Classical decision theory provides several tools and models to solve many of these decision problems. However, most of these models are deterministic and probabilistic models that are not well suited to problems involving uncertainty of a non-probabilistic nature that are common in many real-world situations.

To address these problems and deal with this type of non-probabilistic uncertainty there are different approaches and tools, including fuzzy set theory, Fuzzy Linguistic Approximation, as well as different extensions of fuzzy sets that have improved the flexibility and reliability of classical models. This session aims to provide an opportunity for researchers working in Decision Making under uncertainty using Fuzzy Sets or some of their extensions, to review the state of the art and to present novel and recent results and experiences in the area.

The theory of aggregation functions is a field of research that is attracting increasing interest. Aggregation functions constitute an essential tool for information fusion in multiple applications, such as image processing, classification, machine learning or decision making, among others. Moreover, in recent years, efforts are being made to overcome their limitations, which has led to the introduction of new concepts and ideas. Among them, the notion of pre-aggregation function, which generalizes the classical idea of aggregation function by relaxing the monotonicity conditions, is noteworthy.

In this special session, we will focus on recent theoretical and applied developments around aggregation and pre-aggregation functions, as well as the latest trends in this field.

Aggregation functions are key operators in fuzzy set theory. In this field, advances both from the theoretical and applied point of view have been a constant in the last decades. These operators have proven useful in responding to a growing need to handle large amounts of data and uncertainty and the associated challenges that arise. Families such as t-norms, t-conorms, uninorms, OWAs or Choquet integrals play an important role in fields such as decision making, image processing, fuzzy systems or fuzzy control.

On the other hand, fuzzy implication functions have experienced a boom in recent times with several books and state of the art devoted entirely to these operators. In addition to their theoretical importance in fuzzy set theory, there is a growing interest in the applications of these operators in data mining, approximate reasoning or computing with words, among other fields.

Fuzzy implication functions and aggregation functions are closely related since several families of aggregation functions have been successfully used in the generation of new families of fuzzy implication functions and functional equations where both operators are involved are common. Solving such functional equations provides operators with specific properties useful in certain applications.