Understanding fuzzy measures: measurement of interactions in a bi-dimensional scenario

Abstract

Fuzzy measures are a common occurrence in real-world situations, so understanding them is crucial for making informed decisions based on incomplete or uncertain data. This work describes a study focused on measuring interactions between individuals using a fuzzy measure and representing the results in a bi-dimensional scenario. The method used for this measurement is based on the Shapley value, a well-established mathematical framework for quantifying individual contributions in cooperative game theory and adapted to fuzzy analysis. We propose a conceptually simple solution that allows for a more accurate and reliable assessment of interactions between individuals, with an intuitive interpretation The use of the Shapley value in conjunction with a fuzzy measure allows for a more nuanced understanding of the interactions being analyzed, making this study a valuable contribution to the field.