Two-dimensional Affine Continuous Cellular Automata Solving the Relaxed Density Classification Problem

摘要

The density classification problem is one of the most studied problems in the context of the computational abilities of cellular automata. Since this problem cannot be solved in the classical sense, we consider a weaker version, by slightly relaxing the assumptions on the output specification. In this paper, we discuss this relaxed problem for two-dimensional Affine Continuous Cellular Automata (ACCAs). We focus on finding the most performant rules solving this problem among the density-conserving ones by evaluating ACCAs experimentally for a predefined set of initial configurations.