Fuzzy Cognitive Maps, Extensions and Applicability as an Explanatory Artificial Intelligence Model¶

Ruiz, Y.M., Piñero Pérez, P.Y., Pérez Pupo, I., García Vacacela, R., Al-Subhi, S.H.S. (2024). Fuzzy Cognitive Maps, Extensions and Applicability as an Explanatory Artificial Intelligence Model. In: Piñero Pérez, P.Y., Kacprzyk, J., Bello Pérez, R., Pupo, I.P. (eds) Computational Intelligence in Engineering and Project Management. CIIP 2023. Studies in Computational Intelligence, vol 1134. Springer, Cham. https://doi.org/10.1007/978-3-031-50495-2_2

Abstract

The growth of the prediction capabilities of deep neural networks constitutes one of the elements that has allowed the generalization of these models to dissimilar problems. But in the particular case of decision-making in project management, in addition to the quality of the prediction, it is necessary to know the explanation of the responses. This aims to increase the confidence of the systems in decision-making and agility in project management. The explanation of the answers is also important during project cuts, a process that manifests itself as a multistage sequential decision-making problem. In this research, it is proposed to explore the potential of fuzzy cognitive maps and their extensions, considering the potential of these techniques to represent causal relationships. To carry out this work, a conceptual theoretical framework is developed based on a systematic review. It is identified that there are insufficiencies in the research reported in the bibliography consulted regarding the treatment of indeterminacy and the solution of decision-making problems in project managemen