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Meta-learning: Bayesian or quantum?

Published online by Cambridge University Press:  23 September 2024

Antonio Mastrogiorgio*
Affiliation:
Department of Psychological and Social Sciences, John Cabot University, Rome, Italy mastrogiorgio.antonio@gmail.com www.johncabot.edu https://sites.google.com/site/mastrogiorgioantonio/
*
*Corresponding author.

Abstract

Abundant experimental evidence illustrates violations of Bayesian models across various cognitive processes. Quantum cognition capitalizes on the limitations of Bayesian models, providing a compelling alternative. We suggest that a generalized quantum approach in meta-learning is simultaneously more robust and flexible, as it retains all the advantages of the Bayesian framework while avoiding its limitations.

Information

Type
Open Peer Commentary
Copyright
Copyright © The Author(s), 2024. Published by Cambridge University Press

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