Hostname: page-component-586b7cd67f-t7czq Total loading time: 0 Render date: 2024-11-23T23:09:59.569Z Has data issue: false hasContentIssue false
  • English
  • Français

Keeping Bayesian models rational: The need for an account of algorithmic rationality

Published online by Cambridge University Press:  25 August 2011

David Danks  and
Frederick Eberhardt
David Danks
Affiliation:
Department of Philosophy, Carnegie Mellon University, Pittsburgh, PA 15213. [email protected]://www.hss.cmu.edu/philosophy/faculty-danks.php
Frederick Eberhardt
Affiliation:
Philosophy–Neuroscience–Psychology Program, Washington University in St. Louis, St. Louis, MO 63130. [email protected]://www.artsci.wustl.edu/~feberhar/
Get access Rights & Permissions [Opens in a new window]

Abstract

We argue that the authors’ call to integrate Bayesian models more strongly with algorithmic- and implementational-level models must go hand in hand with a call for a fully developed account of algorithmic rationality. Without such an account, the integration of levels would come at the expense of the explanatory benefit that rational models provide.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 34 , Issue 4 , August 2011 , pp. 197
Copyright
Copyright © Cambridge University Press 2011

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.)

References

Eberhardt, F. & Danks, D. (2011) Confirmation in the cognitive sciences: The problematic case of Bayesian models. Minds and Machines 21(3):389–410.CrossRefGoogle Scholar
Oaksford, M. & Chater, N. (2007) Bayesian rationality: The probabilistic approach to human reasoning. Oxford University Press.CrossRefGoogle Scholar