Title: View{based Cognitive Map Learning by an Autonomous Robot

This paper presents a view{based approach to map learning and navigation in mazes. By means of graph theory we have shown that the view{graph is a suucient representation for map behaviour such as path planning. A neural network for unsupervised learning of the view{graph from sequences of views is constructed. We use a modiied Kohonen (1988) learning rule that transforms temporal sequence (rather than featural similarity) into connectedness. In the main part of the paper, we present a robot implementation of the scheme. The results show that the proposed network is able to support map behaviour in simple environments.