Evolutionary Progress in Heterogenous Cellular Automata (HetCA)

Abstract

Although very controversial in the field of evolutionary biology, the notion of evolutionary progress is nevertheless generally accepted in the field of Artificial Life. In this article we adopt the definition proposed by Shanahan (2012) to study the existence of evolutionary progress in an evolutionary simulation which we call HetCA. HetCA is a heterogeneous cellular automata characterized by its ability to generate open ended long-term evolution. In this study, we measure evolutionary progress on three criteria: the robustness, size and density of generated genotypes. Our results demonstrate that the oldest genotypes in terms of evolutionary time are frequently the most robust, and that phenotypic density is higher for genotypes collected later in the evolutionary process.

Evolution of Heterogeneous Cellular Automata in Fluctuating Environments

“…We showed that HetCA could exhibit long-term phenotypic dynamics, a high variance over very long runs, greater behavioral diversity than classical CA, and "evolutionary progress" (Shanahan, 2012) on three criteria: robustness, size and density of the genotype (Medernach et al, 2015).…”

“…repeats a sequence of states, this sequence must contain a minimum of two states in order to ensure the survival of the genotype-the quiescent state and one of the living states. We chose to limit the comparison to 1 It was shown by Medernach et al (2015) that during the initial iterations of HetCA the MCGs were unlikely to exhibit any viable survival strategy. the 8 previous iterations in order to reduce the computational cost and because the limit of 7 consecutive live iterations before decay involves, for a successful regular phenotype, a maximum periodicity of 7 iterations for the quiescent state.…”