Is human compositionality meta-learned?

IF 16.6 1区 心理学 Q1 BEHAVIORAL SCIENCES Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI:10.1017/S0140525X24000189
Jacob Russin, Sam Whitman McGrath, Ellie Pavlick, Michael J Frank
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引用次数: 0

Abstract

Recent studies suggest that meta-learning may provide an original solution to an enduring puzzle about whether neural networks can explain compositionality - in particular, by raising the prospect that compositionality can be understood as an emergent property of an inner-loop learning algorithm. We elaborate on this hypothesis and consider its empirical predictions regarding the neural mechanisms and development of human compositionality.

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人类的组合方式是元学习的吗?
最近的研究表明,元学习(meta-learning)可能会为神经网络能否解释合成性这一长期谜题提供一种新的解决方案,特别是通过提出合成性可以被理解为内环学习算法的一种新兴属性这一前景。我们将详细阐述这一假设,并考虑它对人类构图性的神经机制和发展的经验预测。
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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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