Integrating similarity-based and explanation-based learning
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Authors
Oosthuizen, GD
Avenant, C
Issue Date
1991
Type
Language
en
Keywords
Artificial intelligence , Machine learning
Alternative Title
Abstract
Recently, there have been various attempts to combine the strengths of
similarity-based learning (SBL) and explanation-based learning (EBL) in a single learning system.
We describe a graph-based learning method called Graph Induction, which is based on the graphical representation of a formal lattice and supports both supervised and unsupervised learning. The method integrates SBL with a weak form of EBL in such a way that the two mechanisms become totally blended. The result is a unified algorithm with both SBL and EBL involved in each step. The domain theory is generated and/or extended as SBL proceeds and employed immediately, through EBL, to guard further learning and thus control the size of the lattice which otherwise has the potential for increasing exponentially.
Description
Citation
Oosthuizen, G.D. & Avenant, C. (1991) Integrating similarity-based and explanation-based learning. Proceedings of the 6th Southern African Computer Symposium, De Overberger Hotel, Caledon, 2-3 July 1991