Research Seminar - November 26, 1999

Abstract

The dominating models of information processes have been based on symbolic representations of information and knowledge. During the last years, a variety of non-symbolic models have been proposed as superior. The prime examples of models within the non-symbolic approach are neural networks. However, the new connectionist models of information processing, to a large extent, lack a higher-level theory of representation. In this paper, conceptual spaces are suggested as an appropriate framework for non-symbolic models. Conceptual spaces consist of a number of 'quality dimensions' which often are derived from perceptual mechanisms. It will be outlined how conceptual spaces can represent various kind of information and how they can be used to describe cognitive processes like concept formation and induction.