Developmental learning for more generic robotic controllers

We describe research in a new area of growing importance: developmental robotics. Inspired by human development, this field is producing novel learning algorithms for the coordination and control of sensory-motor systems. From a consideration of the requirements of autonomy we argue that the developmental approach offers several desirable features and some important advantages. Experimental laboratory systems are described and their implications for autonomous behaviour are discussed