Inhibition of convergence of mimicry rings by low learning abilities of predators

Abstract

Since Müllerian mimicry is more effective, the greater the number of species involved, multiple mimicry rings tend to gradually converge into one large mimicry ring, which then tends to expand. However, in nature, mimicry rings often do not converge into a single ring. It is believed that various factors lead to the diversification of mimicry rings. In this study, we conducted an evolutionary simulation experiment using a multi-agent system (MAS) based on the hypothesis that “predators with low learning ability cannot learn the patterns of toxic prey and continue to prey on species that exhibit Müllerian mimicry." Our aim was to investigate the inhibitory factor of convergence of mimicry rings. We use two types of agent models that make up the MAS: PREY-agent and PREDATOR-agent. Each PREDATOR-agent encounters a PREY-agent randomly at each step, decides whether to prey on the PREY-agent or not based on the pattern of the PREY-agent using its own feed-forward neural network (FFNN); it also uses its FFNN to learn the relationship between the PREY-agent’s pattern and the presence or absence of venom. The PREY-agent determines its own fitness based on the results of whether or not it was preyed upon by PREDATOR-agent, performs genetic evolution based on this fitness, and decodes its own genes to generate patterns. This pattern is generated using a modified L-system. Evolutionary simulation experiments using the MAS showed that the convergence of the mimicry ring is inhibited when the number of neurons in the hidden layer in the PREDATOR-agent’s FFNN is small, i.e., when the learning ability of the PREDATOR-agent is low.