Pseudo-arithmetical operations as a basis for the general measure and integration theory
Information Sciences—Informatics and Computer Science: An International Journal
Precisiated natural language (PNL)
AI Magazine
Modeling Decisions: Information Fusion and Aggregation Operators (Cognitive Technologies)
Modeling Decisions: Information Fusion and Aggregation Operators (Cognitive Technologies)
Aggregation Functions: A Guide for Practitioners
Aggregation Functions: A Guide for Practitioners
Generalized theory of uncertainty (GTU)-principal concepts and ideas
Computational Statistics & Data Analysis
A universal integral as common frame for choquet and Sugeno integral
IEEE Transactions on Fuzzy Systems
Classic Works of the Dempster-Shafer Theory of Belief Functions
Classic Works of the Dempster-Shafer Theory of Belief Functions
On the entropy of fuzzy measures
IEEE Transactions on Fuzzy Systems
Time Series Smoothing and OWA Aggregation
IEEE Transactions on Fuzzy Systems
A measure based approach to the fusion of possibilistic and probabilistic uncertainty
Fuzzy Optimization and Decision Making
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A fundamental task in decision-making is the determination, in the face of uncertain information, of the satisfaction of some criteria in terms of a scalar value. Our objective here is to help support this task. We first discuss the process of selecting an uncertainty model for our knowledge, here we emphasize the tradeoff between functionality of the representation and its ability to model our knowledge, cointention. We next discuss the process of scalarization, determining a single value to represent some uncertain value. Some features required of operations used for scalarization are introduced. We look at the scalarization procedures used in probability theory, the expected value, and that used in possibility theory. We then turn to a more general framework for the representation of uncertain information based on a set measure.