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Computational models of intrinsic motivation for curiosity and creativity

Published online by Cambridge University Press:  21 May 2024

Sophia Becker
Affiliation:
Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland sophia.becker@epfl.ch alireza.modirshanechi@epfl.ch wulfram.gerstner@epfl.ch; https://lcnwww.epfl.ch/gerstner/ School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
Alireza Modirshanechi
Affiliation:
Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland sophia.becker@epfl.ch alireza.modirshanechi@epfl.ch wulfram.gerstner@epfl.ch; https://lcnwww.epfl.ch/gerstner/ School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
Wulfram Gerstner*
Affiliation:
Brain Mind Institute, School of Life Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland sophia.becker@epfl.ch alireza.modirshanechi@epfl.ch wulfram.gerstner@epfl.ch; https://lcnwww.epfl.ch/gerstner/ School of Computer and Communication Sciences, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
*
*Corresponding author.

Abstract

We link Ivancovsky et al.'s novelty-seeking model (NSM) to computational models of intrinsically motivated behavior and learning. We argue that dissociating different forms of curiosity, creativity, and memory based on the involvement of distinct intrinsic motivations (e.g., surprise and novelty) is essential to empirically test the conceptual claims of the NSM.

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

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