abstract = "Designing robots and robot controllers is a highly
complex and often expensive task. However, genetic
programming provides an automated design strategy to
evolve complex controllers based on evolution in
nature. We show that, even with limited computational
resources, genetic programming is able to evolve
efficient robot controllers for corridor following in a
simulation environment. Therefore, a mixed and gradual
form of layered learning is used, resulting in very
robust and efficient controllers. Furthermore, the
controller is successfully applied to real environments
as well.",
notes = "Paper Nr: 26
Dept. of Electrical Energy, Systems and Automation,
Ghent University, Technologiepark 913, Zwijnaarde,
Belgium",