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Challenges of meta-learning and rational analysis in large worlds

Published online by Cambridge University Press:  23 September 2024

Margherita Calderan Open the ORCID record for Margherita Calderan [Opens in a new window]  and
Antonino Visalli Open the ORCID record for Antonino Visalli [Opens in a new window]
Margherita Calderan
Affiliation:
Department of Developmental Psychology and Socialisation, University of Padova, Italy margherita.calderan@phd.unipd.it
Antonino Visalli*
Affiliation:
IRCCS San Camillo Hospital, Venice, Italy antonino.visalli@hsancamillo.it
*
*Corresponding author.
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Abstract

We challenge Binz et al.'s claim of meta-learned model superiority over Bayesian inference for large world problems. While comparing Bayesian priors to model-training decisions, we question meta-learning feature exclusivity. We assert no special justification for rational Bayesian solutions to large world problems, advocating exploring diverse theoretical frameworks beyond rational analysis of cognition for research advancement.

Information

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 47 , 2024 , e148
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Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

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