Abstract. This paper continues our systematic study of an RNAediting computational model of Genetic Algorithms (GA). This model is constructed based on several genetic editing characteristics that are gleaned from the RNA editing system as observed in several organisms. We have expanded the traditional Genetic Algorithm with artificial editing mechanisms as proposed in [11] and [12]. The incorporation of editing mechanisms, which stochastically alter the information encoded in the genotype, provides a means for artificial agents with genetic descriptions to gain greater phenotypic plasticity, which may be environmentally regulated. The systematic study of this artificial genotype editing model has shed some light into the evolutionary implications of RNA editing and how to select proper genotype editors to design more robust GAs. Our results also show promising applications to complex real-world problems. We expect that the framework here developed will both facilitate determining t...