A knowledge acquisition system based on the Cartesian space model

This paper presents a new approach to knowledge acquisition systems. Our knowledge acquisition system is located between artificial intelligence approaches and pattern recognition approaches. The system is based on the Cartesian space model (CSM) which is a mathematical model to treat symbolic data where each sample is described not only by quantitative features but also qualitative and structural features. We compare our knowledge acquisition system with the ID3 symbolic learning system and the backpropagation neural network learning system based on a simple example.