One dimensional nary density classification using two cellular automaton rules
Suppose each site on a one-dimensional chain with periodic boundary condition may take on any one of the states 0, 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.
density classification cellular automaton discrete dynamical system symbolic dynamics