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Universal Bayesian inference?

Published online by Cambridge University Press:  20 August 2002

David Dowe
Affiliation:
Department of Computer Science, Monash University, Clayton, Vic 3800, Australia David.Dowe@infotech.monash.edu.au http://www.cs.monash.edu.au/~dld/
Graham Oppy
Affiliation:
Department of Philosophy, Monash University, Clayton, Vic 3800, Australia Graham.Oppy@arts.monash.edu.au
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Abstract

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We criticise Shepard's notions of “invariance” and “universality,” and the incorporation of Shepard's work on inference into the general framework of his paper. We then criticise Tenenbaum and Griffiths' account of Shepard (1987b), including the attributed likelihood function, and the assumption of “weak sampling.” Finally, we endorse Barlow's suggestion that minimum message length (MML) theory has useful things to say about the Bayesian inference problems discussed by Shepard and Tenenbaum and Griffiths. [Barlow; Shepard; Tenenbaum & Griffiths]

Information

Type
Brief Report
Copyright
© 2001 Cambridge University Press