Learning Mechanisms which Construct Neighbourhood Representations

Learning is currently the focus of much research activity in cognitive science. But, typically, this research is oriented towards either the symbolprocessing paradigm or the connectionist paradigm and therefore tends to generate models of two quite different types. A satisfactory theory of learning will, presumably, deal with the phenomenon in general terms rather than in terms of two special cases, so there would appear to be a need to try to identify abstractions which generalise the two types of model typically produced. The aim of the present paper is to identify one such abstraction. It puts forward a framework in which the behaviours of two symbol-processing learning mechanisms are directly commensurable with the behaviours of three connectionist learning mechanisms and shows that there is at least one theoretical constraint affecting all mechanisms covered by the framework