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人类婴儿的概率推理。

Probabilistic inference in human infants.

机构信息

Department of Psychology, University of California, Berkeley, Berkeley, CA 94720, USA.

出版信息

Adv Child Dev Behav. 2012;43:27-58. doi: 10.1016/b978-0-12-397919-3.00002-2.

Abstract

In this chapter, we review empirical evidence in support of infants' ability to make rudimentary probabilistic inferences. A recent surge of research in cognitive developmental psychology examines whether human learners, from infancy through adulthood, reason in ways consistent with Bayesian inference. However, when exploring this question an important first step is to identify the available inference mechanisms and computational machinery that might allow infants and young children to make inductive inferences. A number of recent studies have asked if infants may be "intuitive statisticians," making inferences about the relationship between samples and populations in both looking-time and choice tasks. Furthermore, infants make these inferences under a variety of sampling conditions and integrate prior domain knowledge into their probability calculations. The competences demonstrated in the reviewed experiments appear to draw on an intuitive probability notion that is early emerging and does not appear to be available for conscious reflection.

摘要

在本章中,我们回顾了支持婴儿进行基本概率推理能力的实证证据。认知发展心理学领域最近涌现出大量研究,旨在探讨从婴儿期到成年期的人类学习者是否以符合贝叶斯推理的方式进行推理。然而,在探讨这个问题时,首先要确定的是可能允许婴儿和幼儿进行归纳推理的可用推理机制和计算机制。最近的一些研究询问婴儿是否可能是“直觉统计学家”,即在观察时间和选择任务中对样本和总体之间的关系进行推断。此外,婴儿在各种抽样条件下进行这些推断,并将先验领域知识纳入其概率计算中。在回顾的实验中表现出的能力似乎依赖于一种直观的概率概念,这种概念很早就出现了,并且似乎无法进行有意识的反思。

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