Gutiérrez García-Pardo, InmaculadaSantos, DanielCastro Cantalejo, JavierGómez González, DanielEspínola Vílchez, María Rosario2024-09-032024-09-032023Gutierrez, I. et al. (2023) «Understanding Fuzzy Measures: Measurement of Interactions in a Bi-Dimensional Scenario», en IEEE International Conference on Fuzzy Systems. Institute of Electrical and Electronics Engineers Inc. Disponible en: https://doi.org/10.1109/FUZZ52849.2023.10309674979-8-3503-3228-5979-8-3503-3229-21544-561510.1109/FUZZ52849.2023.10309674https://hdl.handle.net/20.500.14352/107838Fuzzy 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.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/conference paper1558-4739https://doi.org/10.1109/FUZZ52849.2023.10309674https://ieeexplore.ieee.org/document/10309674restricted access004.6519.813Measurement uncertaintyMachine learningReliability theoryMathematical modelsProposalsNoise measurementGame theoryTeoría de JuegosEstadística1209 Estadística1207.06 Teoría de Juegos1209.03 Análisis de Datos