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Integrating similarity-based and explanation-based learning

Show simple item record Oosthuizen, GD Avenant, C 2018-05-20T01:32:03Z 2018-05-20T01:32:03Z 1992
dc.identifier.citation Oosthuizen GD & Avenant C (1992) Integrating similarity-based and explanation-based learning. South African Computer Journal, Number 6, 1992 en
dc.identifier.issn 2313-7835
dc.description.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. en
dc.language en
dc.language.iso en en
dc.publisher South African Institute of Computer Scientists and Information Technologists en
dc.subject Artificial intelligence en
dc.subject Machine learning en
dc.title Integrating similarity-based and explanation-based learning en
dc.type Article en

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