Hostname: page-component-cb9f654ff-5jtmz Total loading time: 0 Render date: 2025-08-23T03:37:33.086Z Has data issue: false hasContentIssue false
  • English
  • Français

Universal Bayesian inference?

Published online by Cambridge University Press:  20 August 2002

David Dowe  and
Graham Oppy
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
Get access Rights & Permissions [Opens in a new window]

Abstract

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
Information
Behavioral and Brain Sciences , Volume 24 , Issue 4 , August 2001 , pp. 662 - 663
Copyright
© 2001 Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable