Abstract
This chapter introduces the concept of fuzzy world as an ontological basis for modeling complex-adaptive systems. The concept is grounded on a phenomenological analysis of these systems over micro and macro scales. Discussion is developed from a recapitulation of some concepts of complexity science and complex systems modeling. Finally, the argument points out that fuzzy worlds find in fuzzy sets and systems theory a natural epistemological and methodological support.
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Melgarejo, M. (2020). Fuzzy Worlds and the Quest for Modeling Complex-Adaptive Systems. In: Castillo, O., Melin, P., Kacprzyk, J. (eds) Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications. Studies in Computational Intelligence, vol 862. Springer, Cham. https://doi.org/10.1007/978-3-030-35445-9_39
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