The meta-learning toolkit needs stronger constraints.

IF 16.6 1区心理学 Q1 BEHAVIORAL SCIENCES

Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI:10.1017/S0140525X24000104

Erin Grant

引用次数: 0

Abstract

The implementation of meta-learning targeted by Binz et al. inherits benefits and drawbacks from its nature as a connectionist model. Drawing from historical debates around bottom-up and top-down approaches to modeling in cognitive science, we should continue to bridge levels of analysis by constraining meta-learning and meta-learned models with complementary evidence from across the cognitive and computational sciences.

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元学习工具包需要更强的约束。

Binz等人针对元学习的实施，继承了其作为联结主义模型的优点和缺点。借鉴认知科学中自下而上和自上而下建模方法的历史争论，我们应该继续弥合分析的层次，用来自认知科学和计算科学的互补证据来约束元学习和元学习模型。

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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来源期刊

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.