On the hazards of relating representations and inductive biases

The success of models of human behavior based on Bayesian inference over logical formulas or programs is taken as evidence that people employ a “language-of-thought” that has similarly discrete and compositional structure. We argue that this conclusion problematically crosses levels of analysis, ide...

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Bibliographic Details
Published in:The Behavioral and brain sciences 2023-09, Vol.46, p.e275-e275, Article e275
Main Authors: Griffiths, Thomas L., Kumar, Sreejan, McCoy, R. Thomas
Format: Article
Language:English
Subjects:
Algorithms
Bayesian analysis
Cognition & reasoning
Hypotheses
Language
Mathematical models
Neural networks
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Summary:The success of models of human behavior based on Bayesian inference over logical formulas or programs is taken as evidence that people employ a “language-of-thought” that has similarly discrete and compositional structure. We argue that this conclusion problematically crosses levels of analysis, identifying representations at the algorithmic level based on inductive biases at the computational level.
ISSN:0140-525X
1469-1825
DOI:10.1017/S0140525X23002042