作为认知模型的概率编程与元学习。

IF 19.3 1区材料科学 Q1 CHEMISTRY, PHYSICAL

ACS Energy Letters Pub Date : 2024-09-23 DOI:10.1017/S0140525X24000153

Desmond C Ong, Tan Zhi-Xuan, Joshua B Tenenbaum, Noah D Goodman

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引用次数: 0

摘要

我们总结了概率编程作为人类认知的概率、符号和数据驱动方面的统一形式主义所取得的最新进展。我们强调了元学习在灵活性、统计假设和认知推断方面的不同之处。我们建议，元学习方法可以通过考虑联结主义和贝叶斯方法得到进一步加强，而不是只考虑其中一种方法。

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Probabilistic programming versus meta-learning as models of cognition.

We summarize the recent progress made by probabilistic programming as a unifying formalism for the probabilistic, symbolic, and data-driven aspects of human cognition. We highlight differences with meta-learning in flexibility, statistical assumptions and inferences about cogniton. We suggest that the meta-learning approach could be further strengthened by considering Connectionist and Bayesian approaches, rather than exclusively one or the other.

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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.