Evolving Insect Locomotion using Non-uniform Cellular Automata

This article presents a model for the evolution of locomotion behavior in a simulated insect. In our model, locomotion is defined over a discrete state space using non-uniform cellular automata. The architecture of the model is inspired from the distributed model for leg coordination proposed by Cruse. We apply a genetic algorithm to a population of non-uniform cellular automata to evolve locomotion behaviors. We demostrate that this model can be used to evolve several commonly observed gaits of insects. Additionally, we show that the evolutionary process yielded periodic attractors which are invariant from the initial conditions