Evolutionary robotics (ER) is a methodology that uses evolutionary computation to develop controllers for autonomous robots. Algorithms in ER frequently operate on populations of candidate controllers, initially selected from some distribution. This population is then repeatedly modified according to a fitness function. In the case of genetic algorithms (or "GAs"), a common method in evolutionary computation, the population of candidate controllers is repeatedly grown according to crossover, mutation and other GA operatorsand then culled according to the fitness function. The candidate controllers used in ER applications may be drawn from some subset of the set of artificial neural networks, although some applications (including SAMUEL, developed at the Naval Center for Applied Research in