Decision Making under Uncertainty in Soft Computing

Dear Colleagues,

Soft computing is a branch of Artificial Intelligence that focuses on techniques used for the resolution of problems that incorporate incomplete, uncertain and/or imprecise information.

Difficulties in making decisions about real-life problems have motivated the development of decision theory. Fuzzy set theory and its generalizations are fundamental in the processing of imprecise information and reasoning under uncertainty. These theories provide theoretical and practical frameworks that are suitable for modeling in many types of applications.

The purpose of this Special Issue is to gather a collection of articles on cutting-edge advances and developments in this field, which includes, but is not limited to, topics such as: optimization, decision making, aggregation functions, natural language processing, knowledge representation, extensions and generalizations of fuzzy sets, aggregation operations, fuzzy programming, and approximate reasoning. Manuscripts on theoretical foundations and applied developments and related methodologies of soft computing in the domains of economics, medical sciences, engineering, industry, social sciences, and others, are welcome.

Prof. Dr. Gustavo Santos-García
Prof. Dr. José Carlos R. Alcantud
Guest Editors

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