Cellular Automata in an Artificial Life perspective

Artificial Life (AL; [1]) studies all kinds of biological phenomena as they occur in artificial organisms. Neural Networks (NNs; [2]) are commonly used in AL research as computational models of nervous systems that control organisms’ behavior. However, organisms do not only possess nervous systems and other phenotypic traits but also genetic information stored in the nucleus of their cells (genotype). The nervous system is part of the phenotype which is derived from this genotype through a process called development. The information specified in the genotype determines aspects of the nervous system which are expressed as innate behavioral tendencies and predisposition to learn. As a consequence, in AL models NNs tend to be accompanied by genotypes (i.e., genetic algorithms; [3]) and to become members of evolving populations of networks in which genotypes are inherited from parents to offspring.