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Prediction error minimization as a common computational principle for curiosity and creativity

Published online by Cambridge University Press:  21 May 2024

Maxi Becker Open the ORCID record for Maxi Becker [Opens in a new window]  and
Roberto Cabeza Open the ORCID record for Roberto Cabeza [Opens in a new window]
Maxi Becker*
Affiliation:
Department of Psychology, Humboldt University Berlin, Berlin, Germany maxi.becker@gmx.net; maxi.becker@hu-berlin.de
Roberto Cabeza
Affiliation:
Department of Psychology, Humboldt University Berlin, Berlin, Germany maxi.becker@gmx.net; maxi.becker@hu-berlin.de Center for Cognitive Neuroscience, Duke University LSRC Bldg, Durham, NC, USA cabeza@duke.edu https://cabezalab.org/
*
*Corresponding author.
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Abstract

We propose expanding the authors’ shared novelty-seeking basis for creativity and curiosity by emphasizing an underlying computational principle: Minimizing prediction errors (mismatch between predictions and incoming data). Curiosity is tied to the anticipation of minimizing prediction errors through future, novel information, whereas creative AHA moments are connected to the actual minimization of prediction errors through current, novel information.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 47 , 2024 , e93
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Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

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References

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