On the hazards of relating representations and inductive biases
- PMID: 37766644
- DOI: 10.1017/S0140525X23002042
On the hazards of relating representations and inductive biases
Abstract
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.
Comment in
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The language-of-thought hypothesis as a working hypothesis in cognitive science.Behav Brain Sci. 2023 Sep 28;46:e292. doi: 10.1017/S0140525X23002431. Behav Brain Sci. 2023. PMID: 37766639
Comment on
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The best game in town: The reemergence of the language-of-thought hypothesis across the cognitive sciences.Behav Brain Sci. 2022 Dec 6;46:e261. doi: 10.1017/S0140525X22002849. Behav Brain Sci. 2022. PMID: 36471543
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