Meta-learned models as tools to test theories of cognitive development.

IF 16.6 1区 心理学 Q1 BEHAVIORAL SCIENCES Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI:10.1017/S0140525X24000281
Kate Nussenbaum, Catherine A Hartley
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引用次数: 0

Abstract

Binz et al. argue that meta-learned models are essential tools for understanding adult cognition. Here, we propose that these models are particularly useful for testing hypotheses about why learning processes change across development. By leveraging their ability to discover optimal algorithms and account for capacity limitations, researchers can use these models to test competing theories of developmental change in learning.

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将元学习模型作为检验认知发展理论的工具。
Binz 等人认为,元学习模型是理解成人认知的重要工具。在此,我们提出,这些模型对于检验学习过程在整个发展过程中发生变化的原因尤其有用。通过利用这些模型发现最佳算法和考虑能力限制的能力,研究人员可以利用这些模型来检验学习发展变化的竞争性理论。
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来源期刊
Behavioral and Brain Sciences
Behavioral and Brain Sciences 医学-行为科学
CiteScore
1.40
自引率
1.70%
发文量
353
期刊介绍: Behavioral and Brain Sciences (BBS) is a highly respected journal that employs an innovative approach called Open Peer Commentary. This format allows for the publication of noteworthy and contentious research from various fields including psychology, neuroscience, behavioral biology, and cognitive science. Each article is accompanied by 20-40 commentaries from experts across these disciplines, as well as a response from the author themselves. This unique setup creates a captivating forum for the exchange of ideas, critical analysis, and the integration of research within the behavioral and brain sciences, spanning topics from molecular neurobiology and artificial intelligence to the philosophy of the mind.
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