A Model of Biological Differentiation using Flexible APPLY crossover of n-output Binary Decision Diagram

In this paper, we propose an evolution model of biological differentiation based on differences of ecological traits and reproductive isolation. We use a gene expression system n-BDD (n-output Binary Decision Diagram) proposed in order to express and optimize agent's behavior. Although the system is suitable for behavior models of agents, a conventional crossover for an n-BDD has a week point. It is needed to fix each rank of variables. Each rank of variables indicates each priority of perceptual information and it should not be fixed. This paper proposes Flexible APPLY crossover, in which the rank of variables can be changed according to each environments. Using this crossover we model a more realistic ecosystem simulation where each agents can change each rank of variables at generation shift so as to adapt themselves to the environment, we observed agents becoming to differentiate into two types. In addition, we found that the biological differentiation is caused by agents adapting strategies to their ecological traits and is accelerated by the reproductive isolation.