We present two empirical studies on the design of control software for robot swarms. In Study A, Vanilla and EvoStick, two previously published automatic design methods, are compared with human designers. The comparison is performed on five swarm robotics tasks that are different from those on which Vanilla and EvoStick have been previously tested. The results show that, under the experimental conditions considered, Vanilla performs better than EvoStick, but it is not able to outperform human designers. The results indicate that Vanilla 's weak element is the optimization algorithm employed to search the space of candidate designs. To improve over Vanilla and with the final goal of obtaining an automatic design method that performs better than human designers, we introduce Chocolate, which differs from Vanilla only in the fact that it adopts a more powerful optimization algorithm. In Study B, we perform an assessment of Chocolate. The results show that, under the experimental conditions considered, Chocolate outperforms both Vanilla and the human designers. Chocolate is the first automatic design method for robot swarms that, at least under specific experimental conditions, is shown to outperform a human designer.
