Suppr超能文献

24个月大婴儿基于概率事件的因果学习:一种行为测量方法。

Causal learning from probabilistic events in 24-month-olds: an action measure.

作者信息

Waismeyer Anna, Meltzoff Andrew N, Gopnik Alison

机构信息

Institute for Learning & Brain Sciences, University of Washington, USA.

出版信息

Dev Sci. 2015 Jan;18(1):175-82. doi: 10.1111/desc.12208. Epub 2014 Jul 16.

Abstract

How do young children learn about causal structure in an uncertain and variable world? We tested whether they can use observed probabilistic information to solve causal learning problems. In two experiments, 24-month-olds observed an adult produce a probabilistic pattern of causal evidence. The toddlers then were given an opportunity to design their own intervention. In Experiment 1, toddlers saw one object bring about an effect with a higher probability than a second object. In Experiment 2, the frequency of the effect was held constant, though its probability differed. After observing the probabilistic evidence, toddlers in both experiments chose to act on the object that was more likely to produce the effect. The results demonstrate that toddlers can learn about cause and effect without trial-and-error or linguistic instruction on the task, simply by observing the probabilistic patterns of evidence resulting from the imperfect actions of other social agents. Such observational causal learning from probabilistic displays supports human children's rapid cultural learning.

摘要

幼儿如何在一个不确定且多变的世界中学习因果结构?我们测试了他们是否能够利用观察到的概率信息来解决因果学习问题。在两项实验中,24个月大的幼儿观察到一名成年人产生了一种概率性的因果证据模式。然后,这些幼儿有机会设计自己的干预措施。在实验1中,幼儿看到一个物体产生某种效果的概率高于第二个物体。在实验2中,效果的频率保持不变,但其概率不同。在观察了概率证据后,两项实验中的幼儿都选择对更有可能产生该效果的物体采取行动。结果表明,幼儿无需通过反复试验或关于该任务的语言指导,仅通过观察其他社会行为者不完美行动所产生的概率证据模式,就能学习因果关系。这种从概率展示中进行的观察性因果学习支持了人类儿童快速的文化学习。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验