Using a Genetic Algorithm to Replicate Allopatric Speciation

• Published in: 2019 IEEE Congress on Evolutionary Computation (CEC) pp. 1846 - 1851
• Main Authors: Parker, Gary B., Edwards, Thomas B.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.06.2019
• Subjects: Agent Modeling; Allopatric; Artificial Life; Bioinspired; Biological cells; Color; Evolutionary computation; Genetic Algorithm; Genetic algorithms; Rule Base; Sociology; Speciation; Statistics; Sympatric
• DOI: 10.1109/CEC.2019.8790207

In this paper we describe a method using genetic algorithms to replicate natural allopatric speciation. There are many versions of evolutionary computation (EC) that have some characteristics of speciation, but none that match natural processes. In an effort to develop such a form of EC, we created a simple model that we used to experiment in developing an EC that mimics natural speciation. Our long term goal for speciation is to have a single population eventually become two populations that are reproductively isolated even though they reside in the same environment. In previous work we developed an environment where we replicated adaptation, survival of the fittest, and migration of a population. In this paper, we report on research where we used this environment to explore the possibility of speciation. We use a genetic algorithm that alters the agents in the environment as we allow a population of intermixing individuals to develop and become established. We then add a physical barrier that separates the individuals in the population and then remove the barrier after several generations to see if the initially single population becomes two reproductively isolated populations despite no longer being physically isolated. In this way we were able to replicate the initial stages of allopatric speciation.