Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/2372
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dc.contributor.authorPhelps, R I-
dc.contributor.authorMusgrove, P B-
dc.coverage.spatial24en
dc.date.accessioned2008-06-06T13:15:40Z-
dc.date.available2008-06-06T13:15:40Z-
dc.date.issued1985-
dc.identifier.citationMaths Technical Papers (Brunel University). January 1985, pp 1-19en
dc.identifier.urihttp://bura.brunel.ac.uk/handle/2438/2372-
dc.description.abstractThis paper presents an overview of a research programme on machine learning which is based on the fundamental process of categorization. This work draws upon the psychological theory of prototypical concepts . This theory is that concepts learnt naturally from interaction with the environment (basic categories) are not structured or defined in logical terms but are clustered in accordance with their similaritry to a central prototype, representing the "most typical" member. A structure of a computer model designed to achieve categorization is outlined and the knowledge representational forms and developmental learning associated with this approach are discussed.en
dc.format.extent125100 bytes-
dc.format.mimetypeapplication/pdf-
dc.language.isoen-
dc.publisherBrunel Universityen
dc.relation.ispartofBrunel University Mathematics Technical Papers collection;-
dc.relation.ispartofseries;TR/02/85-
dc.subjectlearningen
dc.subjectcategorizationen
dc.subjectprototypesen
dc.subjectknowledge representationen
dc.titleA prototypical approach to machine learningen
dc.typeResearch Paperen
Appears in Collections:Dept of Mathematics Research Papers
Mathematical Sciences

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