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Fuzzy Worlds and the Quest for Modeling Complex-Adaptive Systems

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Intuitionistic and Type-2 Fuzzy Logic Enhancements in Neural and Optimization Algorithms: Theory and Applications

Part of the book series: Studies in Computational Intelligence ((SCI,volume 862))

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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Author information

Authors and Affiliations

  1. Universidad Distrital Francisco José de Caldas, Carrera 7a no 40-53 piso 5, Bogotá, DC, Colombia

    Miguel Melgarejo

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  1. Miguel Melgarejo
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Correspondence to Miguel Melgarejo .

Editor information

Editors and Affiliations

  1. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Oscar Castillo

  2. Division of Graduate Studies and Research, Tijuana Institute of Technology, Tijuana, Baja California, Mexico

    Patricia Melin

  3. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

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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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