元学习的难题在于学习什么。

IF 16.6 1区心理学 Q1 BEHAVIORAL SCIENCES

Behavioral and Brain Sciences Pub Date : 2024-09-23 DOI:10.1017/S0140525X24000268

Yosef Prat, Ehud Lamm

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引用次数: 0

摘要

Binz等人强调了元学习的潜力，它不仅能大大提高人工智能算法的灵活性，还能比传统学习方法更准确地逼近人类行为。我们希望强调隐藏在这两个目标之下的一个基本问题，并反过来提出元学习中所需的 "元 "概念的另一个视角：知道要学什么。

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The hard problem of meta-learning is what-to-learn.

Binz et al. highlight the potential of meta-learning to greatly enhance the flexibility of AI algorithms, as well as to approximate human behavior more accurately than traditional learning methods. We wish to emphasize a basic problem that lies underneath these two objectives, and in turn suggest another perspective of the required notion of "meta" in meta-learning: knowing what to learn.

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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.