Machine Learning

, Volume 27, Issue 3, pp 241–257 | Cite as

Using Background Knowledge to Build Multistrategy Learners

  • Claude Sammut


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 that can refer to knowledge provided by the user or learned during 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.

Multistrategy learning inductive logic programming background knowledge knowledge representation 


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Copyright information

© Kluwer Academic Publishers 1997

Authors and Affiliations

  • Claude Sammut
    • 1
  1. 1.School of Computer Science and EngineeringUniversity of New South WalesSydneyAustralia

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