Minds and Machines 21 (3):389-410 (2011)
|Abstract||Bayesian models of human learning are becoming increasingly popular in cognitive science. We argue that their purported confirmation largely relies on a methodology that depends on premises that are inconsistent with the claim that people are Bayesian about learning and inference. Bayesian models in cognitive science derive their appeal from their normative claim that the modeled inference is in some sense rational. Standard accounts of the rationality of Bayesian inference imply predictions that an agent selects the option that maximizes the posterior expected utility. Experimental confirmation of the models, however, has been claimed because of groups of agents that probability match the posterior. Probability matching only constitutes support for the Bayesian claim if additional unobvious and untested (but testable) assumptions are invoked. The alternative strategy of weakening the underlying notion of rationality no longer distinguishes the Bayesian model uniquely. A new account of rationality—either for inference or for decision-making—is required to successfully confirm Bayesian models in cognitive science|
|Keywords||Bayesian modeling Rationality Levels of explanation Methodology in cognitive science|
|Categories||categorize this paper)|
|Through your library||Configure|
Similar books and articles
M. Colombo & P. Series (2012). Bayes in the Brain--On Bayesian Modelling in Neuroscience. British Journal for the Philosophy of Science 63 (3):697-723.
Giuseppe Boccignone & Roberto Cordeschi, Bayesian Models and Simulations in Cognitive Science. Workshop Models and Simulations 2, Tillburg, NL.
Branden Fitelson (2010). The Wason Task(s) and the Paradox of Confirmation. Philosophical Perspectives 24 (1):207-241.
Sean Fulop & Nick Chater (2013). Editors' Introduction: Why Formal Learning Theory Matters for Cognitive Science. Topics in Cognitive Science 5 (1):3-12.
David Christensen (1992). Confirmational Holism and Bayesian Epistemology. Philosophy of Science 59 (4):540-557.
Joseph L. Austerweil & Thomas L. Griffiths (2011). Seeking Confirmation Is Rational for Deterministic Hypotheses. Cognitive Science 35 (3):499-526.
Vincenzo Crupi, Roberto Festa & and Tommaso Mastropasqua (2008). Bayesian Confirmation by Uncertain Evidence: A Reply to Huber . British Journal for the Philosophy of Science 59 (2):201-211.
Johan Kwisthout, Todd Wareham & Iris van Rooij (2011). Bayesian Intractability Is Not an Ailment That Approximation Can Cure. Cognitive Science 35 (5):779-784.
Branden Fitelson (2002). Putting the Irrelevance Back Into the Problem of Irrelevant Conjunction. Philosophy of Science 69 (4):611-622.
Miklós Rédei (1992). When Can Non-Commutative Statistical Inference Be Bayesian? International Studies in the Philosophy of Science 6 (2):129 – 132.
Miklós Rédei (1992). When Can Non‐Commutative Statistical Inference Be Bayesian? International Studies in the Philosophy of Science 6 (2):129-132.
Daniel Steel (2007). Bayesian Confirmation Theory and the Likelihood Principle. Synthese 156 (1):53 - 77.
Patrick Maher (2010). Bayesian Probability. Synthese 172 (1):119 - 127.
Branden Fitelson (1999). The Plurality of Bayesian Measures of Confirmation and the Problem of Measure Sensitivity. Philosophy of Science 66 (3):378.
Added to index2011-05-19
Total downloads23 ( #60,137 of 722,744 )
Recent downloads (6 months)1 ( #60,247 of 722,744 )
How can I increase my downloads?