English

One Dimensional $n$ary Density Classification Using Two Cellular Automaton Rules

adap-org 2015-06-24 v1 Adaptation and Self-Organizing Systems

Abstract

Suppose each site on a one-dimensional chain with periodic boundary condition may take on any one of the states 0,1,...,n10,1,..., n-1, can you find out the most frequently occurring state using cellular automaton? Here, we prove that while the above density classification task cannot be resolved by a single cellular automaton, this task can be performed efficiently by applying two cellular automaton rules in succession.

Keywords

Cite

@article{arxiv.adap-org/9810006,
  title  = {One Dimensional $n$ary Density Classification Using Two Cellular Automaton Rules},
  author = {H. F. Chau and L. W. Siu and K. K. Yan},
  journal= {arXiv preprint arXiv:adap-org/9810006},
  year   = {2015}
}

Comments

Revtex, 4 pages, uses amsfonts