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Networks of Polarized Evolutionary Processors Are Computationally Complete

  • Fernando Arroyo
  • Sandra Gómez Canaval
  • Victor Mitrana
  • Ştefan Popescu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8370)

Abstract

In this paper, we consider the computational power of a new variant of networks of evolutionary processors which seems to be more suitable for a software and hardware implementation. Each processor as well as the data navigating throughout the network are now considered to be polarized. While the polarization of every processor is predefined, the data polarization is dynamically computed by means of a valuation mapping. Consequently, the protocol of communication is naturally defined by means of this polarization. We show that tag systems can be simulated by these networks with a constant number of nodes, while Turing machines can be simulated, in a time-efficient way, by these networks with a number of nodes depending linearly on the tape alphabet of the Turing machine.

Keywords

Turing Machine Hybrid Network Communication Step Input Word Substitution Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Fernando Arroyo
    • 1
  • Sandra Gómez Canaval
    • 1
  • Victor Mitrana
    • 2
  • Ştefan Popescu
    • 3
  1. 1.Department of Languages, Projects and Computer Information SystemsUniversity School of Informatics, Polytechnic University of MadridMadridSpain
  2. 2.Department of Organization and Structure of InformationUniversity School of Informatics, Polytechnic University of MadridMadridSpain
  3. 3.Faculty of Mathematics and Computer ScienceUniversity of BucharestBucharestRomania

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