抄録
This paper presents a mutation-based evolutionary algorithm that evolves genes for regulating developmental timings of phenotypic values, which is meant to bring different evolution speed to each phenotypic variable. A genotype in the evolutionary algorithm time-sequentially generates a given number of entire phenotypes and then finishes its life at each generation. Each gene represents a cycle time of changing a probability for determining its corresponding phenotypic value in a life span of the genotype. This cycle time can be considered a sort of information on developmental timing. This paper also discusses a new approach to depicting an evolutionary optimization process. The approach depicts an evolutionary optimization process as change in a network topology that emerges in the process. An evolutionary optimization process involves identification of linkage between variables, and ability of an evolutionary algorithm in identifying the linkage influences the search efficiency. Therefore, network structures formed by using the identified linkage information in the evolutionary process draw how the evolutionary algorithm solves a given optimization problem. The experimental results show that evolving developmental timings helps to sequentially solve problems with linkage between variables and also that power-law-like network topologies emerge in the optimization process of the mutation-based evolutionary algorithm for any problems used.
