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An Analytical Formulation for Cellular Automata (CA) Based Solution of Density Classification Task (DCT)

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Cellular Automata (ACRI 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4173))

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Abstract

This paper presents an analytical solution for Density Classification Task (DCT) with an n cell inhomogeneous Cellular Automata represented by its Rule Vector (RV) <R 0 R 1 R 2 ⋯R i ⋯R n − − 1>, where rule R i is employed on i th cell (i=0,1,2,⋯(n-1)). It reports the Best Rule Vector (BRV) for solution of DCT. The concept of Rule Vector Graph (RVG) has provided the framwork for the solution. RVG derived from the RV of a CA can be analyzed to derive the Best Rule Vector (BRV) consisting of only rule 232 and 184 (or 226) for 3-neighborhood CA and their equivalent rules for k-neighborhood CA (k>3). The error analysis of the solution has been also reported.

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Authors and Affiliations

  1. Cellular Automata Research Lab (CARL), EM 4/1, Salt Lake-V, W.B., 700091, India

    Nirmalya Sundar Maiti, Shiladitya Munshi & P. Pal Chaudhuri

Authors
  1. Nirmalya Sundar Maiti
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  2. Shiladitya Munshi
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  3. P. Pal Chaudhuri
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Editor information

Editors and Affiliations

  1. Laboratory of Mathematics, Physics and Systems, University of Perpignan, 52, Paul Alduy Avenue, 66860, Perpignan, Cedex, France

    Samira El Yacoubi

  2. Computer Science Department, University of Geneva, Switzerland

    Bastien Chopard

  3. Research Center on Complex Systems and Artificial Intelligence (CSAI) Department of Computer Science, Systems and Communication (DISCo), University of Milan, Bicocca viale Sarca, 336, 20126, Milan, (Italy)

    Stefania Bandini

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© 2006 Springer-Verlag Berlin Heidelberg

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Maiti, N.S., Munshi, S., Chaudhuri, P.P. (2006). An Analytical Formulation for Cellular Automata (CA) Based Solution of Density Classification Task (DCT). In: El Yacoubi, S., Chopard, B., Bandini, S. (eds) Cellular Automata. ACRI 2006. Lecture Notes in Computer Science, vol 4173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11861201_20

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  • DOI: https://doi.org/10.1007/11861201_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40929-8

  • Online ISBN: 978-3-540-40932-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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