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Wavefront Cellular Learning Automata: A New Learning Paradigm

  • Alireza RezvanianEmail author
  • Behnaz Moradabadi
  • Mina Ghavipour
  • Mohammad Mehdi Daliri Khomami
  • Mohammad Reza Meybodi
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 820)

Abstract

The wavefront cellular learning automata (WCLA), which is a generalization of asynchronous cellular learning automata equipped with a diffusion capability, is a new recently introduced model for dynamic environments such as social and information networks. The WCLA as a collection of connected learning automata mapped to a structure and uses the waves on this structure to diffuse state changes of the learning automata. The diffusion ability of WCLA opens a new learning paradigm for solving many real problems in online, non-deterministic, dynamic, distributed or decentralized environments such as online social networks, cloud computing, internet of things and Blockchain technologies. In this chapter, we first provide a brief overview on cellular learning automata models and then introduce the WCLA framework as an optimization tool. The mathematical analysis on behavior of WCLA also is provided as well.

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Alireza Rezvanian
    • 1
    • 2
    Email author
  • Behnaz Moradabadi
    • 2
  • Mina Ghavipour
    • 2
  • Mohammad Mehdi Daliri Khomami
    • 2
  • Mohammad Reza Meybodi
    • 2
  1. 1.School of Computer ScienceInstitute for Research in Fundamental Sciences (IPM)TehranIran
  2. 2.Computer Engineering and Information Technology DepartmentAmirkabir University of Technology (Tehran Polytechnic)TehranIran

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