Incremental learning by VSF network and its chaotic effects

When a system tries to recognize its external world, it should segment information on the ´world´. In this paper, we propose the vibration synchronize function network (VSF-network) that is a neural network model for segmenting information from the external world. We start with a discussion of the relation of information encoded into neural networks and its situation. In the next paragraph an overview of VSF-network and learning algorithm of VSF-network are given. Our VSF-network has been applied for the behavior acquisition of a rover avoiding obstacles. Finally, we discuss performances of VSF-network observed in this application.