Lifetimes of Migration Behavior

This paper tests a Particle Swarm Optimization (PSO) method as a means of modeling the migratory behavior of a flock of artificial birds (agents). The objective is to test the impact of agent lifetime length upon migration behavior, with respect to evolutionary (genetic) and cultural (lifetime) learning. This research tests biological hypotheses that relate an agent (organism) lifetime duration to genetic and lifetime learning. That is, the migration behavior of short lived agents tends to be genetically encoded, whereas, the migration behavior of relatively long lived agents tends to be learned during their lifetimes. In the context of an Agent Based Model, this study simulates various agent lifetime lengths and examines the impact upon the flock’s collective migration behavior. Results indicate that genetic and lifetime learning yields a higher rate of successful migration for a specific lifetime length