Using Background Knowledge to Build Multistrategy Learners

Third International Conference on Multistrategy Learning

Volume

Third International Conference on Multistrategy Learning

Contents

This paper discusses the role that background knowledge can play in building flexible multistrategy learning systems. We contend that a variety of learning strategies can be embodied in the background knowledge provided to a general purpose learning algorithm. To be effective, the general purpose algorithm must have a mechanism for learning new concept descriptions which can refer to knowledge provided by the user or learned from some other task. The method of knowledge representation is a central problem in designing such a system since it should be possible to specify background knowledge in such a way that the learner can apply its knowledge to new information.