Evolving neural controllers that elicit nontrivial behaviors using a developmental process

Recently, evolutionary robotics (ER) has been attracting a lot of attention in the field of robotics artificial life and so on. ER approaches are expected to provide feasible methods to design controllers for autonomous mobile robots with less human intervention. However, most of the conventional studies in ER have been aiming at obtaining very simple (trivial) behaviors such as obstacle avoiding, wall following, and target approaching. To make the ER approach more fruitful, we should pay close attention to obtaining nontrivial behaviors. Based on these considerations, in this paper we propose a method for obtaining nontrivial behaviors using a developmental process with a carefully arranged grafting method. To verify the validity, we apply our idea to the construction of neural controllers that can cope with rough terrain. This work was presented, in part, at the Third International Symptosium on Artificial Life and Robotics, Oita, Japan, January 19–21, 1998