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Being Realist about Bayes, and the Predictive Processing Theory of Mind

Colombo, Matteo and Elkin, Lee and Hartmann, Stephan (2018) Being Realist about Bayes, and the Predictive Processing Theory of Mind. [Preprint]

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Abstract

A number of naturalistic philosophers of mind endorse a realist attitude towards the results of Bayesian cognitive science. This realist attitude is currently unwarranted, however. It is not obvious that Bayesian models possess special epistemic virtues over alternative models of mental phenomena involving uncertainty. In particular, the Bayesian approach in cognitive science is not more simple, unifying and rational than alternative approaches; and it not obvious that the Bayesian approach is more empirically adequate than alternatives. It is at least premature, then, to assert that mental phenomena involving uncertainty are best explained within the Bayesian approach. To continue on with an exclusive praise for Bayes would be dangerous as it risks monopolizing the center of attention, leading to the neglect of different but promising formal approaches. Naturalistic philosophers of mind would be wise instead to endorse an agnostic, instrumentalist attitude towards Bayesian cognitive science to correct their mistake.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Colombo, Matteom.colombo@uvt.nl
Elkin, Leeljelkin3@gmail.com
Hartmann, StephanS.Hartmann@lmu.de
Keywords: Bayesian cognitive science; representing uncertainty; naturalistic philosophy of mind; scientific realism; underdetermination thesis
Subjects: Specific Sciences > Cognitive Science
General Issues > Confirmation/Induction
General Issues > Models and Idealization
Specific Sciences > Probability/Statistics
Depositing User: Dr. Lee Elkin
Date Deposited: 12 Feb 2018 14:03
Last Modified: 12 Feb 2018 14:03
Item ID: 14380
Subjects: Specific Sciences > Cognitive Science
General Issues > Confirmation/Induction
General Issues > Models and Idealization
Specific Sciences > Probability/Statistics
Date: February 2018
URI: http://philsci-archive.pitt.edu/id/eprint/14380

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