Evolutionary growth of genomes for the development and replication of multicellular organisms with indirect encoding

The genomes of biological organisms are not fixed in size. They evolved and diverged into different species acquiring new genes and thus having different lengths. In a way, biological genomes are the result of a self-assembly process where more complex phenotypes could benefit by having larger genomes in order to survive and adapt. In the artificial domain, evolutionary and developmental systems often have static size genomes, e.g. chosen beforehand by the system designer by trial and error or estimated a priori with complicated heuristics. As such, the maximum evolvable complexity is predetermined, in contrast to open-ended evolution in nature. In this paper, we argue that artificial genomes may also grow in size during evolution to produce high-dimensional solutions incrementally. We propose an evolutionary growth of genome representations for artificial cellular organisms with indirect encodings. Genomes start with a single gene and acquire new genes when necessary, thus increasing the degrees of freedom and expanding the available search-space. Cellular Automata (CA) are used as test bed for two different problems: replication and morphogenesis. The chosen CA encodings are a standard developmental table and an instruction based approach. Results show that the proposed evolutionary growth of genomes' method is able to produce compact and effective genomes, without the need of specifying the full set of regulatory configurations.