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Integrative learning in the lens of meta-learned models of cognition: Impacts on animal and human learning outcomes

Published online by Cambridge University Press:  23 September 2024

Bin Yin Open the ORCID record for Bin Yin [Opens in a new window] ,
Xi-Dan Xiao Open the ORCID record for Xi-Dan Xiao [Opens in a new window] ,
Xiao-Rui Wu Open the ORCID record for Xiao-Rui Wu [Opens in a new window]  and
Rong Lian Open the ORCID record for Rong Lian [Opens in a new window]
Bin Yin*
Affiliation:
School of Psychology, Fujian Normal University, Fuzhou, China. [email protected] [email protected] [email protected] [email protected]
Xi-Dan Xiao
Affiliation:
School of Psychology, Fujian Normal University, Fuzhou, China. [email protected] [email protected] [email protected] [email protected]
Xiao-Rui Wu
Affiliation:
School of Psychology, Fujian Normal University, Fuzhou, China. [email protected] [email protected] [email protected] [email protected]
Rong Lian
Affiliation:
School of Psychology, Fujian Normal University, Fuzhou, China. [email protected] [email protected] [email protected] [email protected]
*
*Corresponding author.
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Abstract

This commentary examines the synergy between meta-learned models of cognition and integrative learning in enhancing animal and human learning outcomes. It highlights three integrative learning modes – holistic integration of parts, top-down reasoning, and generalization with in-depth analysis – and their alignment with meta-learned models of cognition. This convergence promises significant advances in educational practices, artificial intelligence, and cognitive neuroscience, offering a novel perspective on learning and cognition.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 47 , 2024 , e169
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Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

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