Guided Self-organisation for Autonomous Robot Development

Abstract. The paper presents a method to guide the self-organised development of behaviours of autonomous robots. In earlier publications we demonstrated how to use the homeokinesis principle and dynamical systems theory to obtain self-organised playful but goal-free behaviour. Now we extend this framework by reinforcement signals. We validate the mechanisms with two experiment with a spherical robot. The first experiment aims at fast motion, where the robot reaches on average about twice the speed of a not reinforcement robot. In the second experiment spinning motion is rewarded and we demonstrate that the robot successfully develops pirouettes and curved motion which only rarely occur among the natural behaviours of the robot. Key words: autonomous robots, self-organised behaviour, reinforcement learning, developmental robotics, homeokinesis

• Type: Conference
• Year: 2007
• Where: ECAL
• Authors: Georg Martius, J. Michael Herrmann, Ralf Der
• Keywords: Artificial Intelligence, Autonomous Robots, ECAL 2007, Self-organised, Self-organised Development