emergent mating topologies in spatially structured genetic algorithms
The application of network analysis to emergent mating topologies in spatially structured genetic algorithms is presented in this preliminary study as a framework for inferring evolutionary dynamics in recombinant evolutionary search. Emergent mating topologies of populations evolving on regular, scale-free, and small-world imposed spatial topologies are analyzed. When the population evolves on a scale-free imposed spatial topology, the topology of mating interactions is also found to be scale-free. However, due to the random initial placement of individuals in the spatial topology, the scale-free mating topology lacks correlation between fitness and vertex connectivity, resulting in highly variable convergence rates. Scale-free mating topologies are also shown to emerge on regular imposed spatial topologies under high selection pressure. Since these scale-free emergent mating topologies self-organize such that the most-fit individuals are inherently located in highly connected vertices, such emergent mating topologies are shown to promote rapid convergence on the test problem considered herein. The emergent mating topologies of populations evolving on small-world imposed spatial topologies are not found to possess scale-free or small-world characteristics. However, due to the decrease in the characteristic path length of the emergent mating topology, the rate of population convergence is shown to increase as the imposed spatial topology is tuned from regular to small-world.
emergence mating topologies genetic algorithms network