Evolutionary Design of Rule-Changing Cellular Automata guided by Parameter indicating Propagation of Information

A method for designing the transition rules ofcellular automata using genetic algorithms is described.Rule-changing cellular automata are expected to performdensity classification tasks more effectively thanordinary cellular automata. We propose a method fordesigning high performance rule-changing cellular automata.This method uses a new parameter that indicatesthe propagation of information. Experimental results fordensity classification tasks show that the proposed methodperforms better than the previous method.