将元学习模型作为检验认知发展理论的工具。

IF 19.3 1区材料科学 Q1 CHEMISTRY, PHYSICAL ACS Energy Letters Pub Date : 2024-09-23 DOI:10.1017/S0140525X24000281

Kate Nussenbaum, Catherine A Hartley

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引用次数: 0

摘要

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。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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

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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来源期刊

ACS Energy Letters Energy-Renewable Energy, Sustainability and the Environment

CiteScore

31.20

自引率

5.00%

发文量

469

审稿时长

1 months

期刊介绍： ACS Energy Letters is a monthly journal that publishes papers reporting new scientific advances in energy research. The journal focuses on topics that are of interest to scientists working in the fundamental and applied sciences. Rapid publication is a central criterion for acceptance, and the journal is known for its quick publication times, with an average of 4-6 weeks from submission to web publication in As Soon As Publishable format. ACS Energy Letters is ranked as the number one journal in the Web of Science Electrochemistry category. It also ranks within the top 10 journals for Physical Chemistry, Energy & Fuels, and Nanoscience & Nanotechnology. The journal offers several types of articles, including Letters, Energy Express, Perspectives, Reviews, Editorials, Viewpoints and Energy Focus. Additionally, authors have the option to submit videos that summarize or support the information presented in a Perspective or Review article, which can be highlighted on the journal's website. ACS Energy Letters is abstracted and indexed in Chemical Abstracts Service/SciFinder, EBSCO-summon, PubMed, Web of Science, Scopus and Portico.