Affinity Classification Problem by Stochastic Cellular Automata

Abstract

This paper introduces the affinity classification problem, which is a generalization of the density classification problem. To solve this problem, we introduce temporally stochastic cellular automata where two rules are stochastically applied in each step on all cells of the automata. Our model is defined on a two-dimensional grid having affection capability. We show that this model can be used in several applications, such as modeling self-healing systems.