Evolvable cellular classifiers

Cellular automata are well-known for their self-organizing and dynamic behaviors in the field of artificial life. This paper addresses a new neuronic architecture, called an evolvable cellular classifier, which evolves by means of genetic rules (chromosomes) in nonuniform cellular automata. An evolvable cellular classifier is primarily based on cellular programming, but its mechanism is simpler because it utilizes only mutations for its main genetic operators, and it resembles the Hopfield network. Therefore, desirable bit patterns can be obtained through evolutionary processes for just one individual agent. As a result, evolvable hardware is derived which is applicable to the classification of bit-string information