Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/2372
Title: A prototypical approach to machine learning
Authors: Phelps, R I
Musgrove, P B
Keywords: learning;categorization;prototypes;knowledge representation
Issue Date: 1985
Publisher: Brunel University
Citation: Maths Technical Papers (Brunel University). January 1985, pp 1-19
Series/Report no.: ;TR/02/85
Abstract: This 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.
URI: http://bura.brunel.ac.uk/handle/2438/2372
Appears in Collections:Mathematical Science
Dept of Mathematics Research Papers

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