APPLICATIONS OF MACHINE LEARNING - TOWARDS KNOWLEDGE SYNTHESIS

This paper shows, by discussing a number of Machine Learning (ML) appl ications, that the existing ML techniques can be effectively applied i n knowledge acquisition for expert systems, thereby alleviating the kn own knowledge acquisition bottleneck. Analysis in domains of practical interest indicates that the performance accuracy of knowledge induced through learning from examples compares very favourably with the accu racy of best human experts. Also, in addition to accuracy, there are e ncouraging examples regarding the clarity and meaningfulness of induce d knowledge. This points towards automated knowledge synthesis, althou gh much further research is needed in this direction. The state of the art of some approaches to Machine Learning is assessed relative to th eir practical applicability and the characteristics of a problem domai n.