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Linking meta-learning to meta-structure

Published online by Cambridge University Press:  23 September 2024

Malte Schilling Open the ORCID record for Malte Schilling [Opens in a new window] ,
Helge J. Ritter  and
Frank W. Ohl
Malte Schilling*
Affiliation:
Autonomous Intelligent Systems Group, Computer Science Department, University of Münster, Münster, Germany malte.schilling@uni-muenster.de https://www.uni-muenster.de/AISystems/
Helge J. Ritter
Affiliation:
Neuroinformatics Group Faculty of Technology/CITEC, Bielefeld University, Bielefeld, Germany helge@techfak.uni-bielefeld.de https://ni.www.techfak.uni-bielefeld.de/people/helge/
Frank W. Ohl
Affiliation:
Department of Systems Physiology of Learning, Leibniz Institute for Neurobiology, Magdeburg, Germany frank.ohl@lin-magdeburg.de Institute of Biology, Otto-von-Guericke University, Magdeburg, Germany https://www.ovgu.de/Ohl.html
*
*Corresponding author.
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Abstract

We propose that a principled understanding of meta-learning, as aimed for by the authors, benefits from linking the focus on learning with an equally strong focus on structure, which means to address the question: What are the meta-structures that can guide meta-learning?

Information

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 47 , 2024 , e164
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Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

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References

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