Department of Psychology, Rutgers University at Newark, Newark, NJ 07102 USA.
University of Waterloo, 200 University Avenue West, Waterloo, ON, N2L 3G1, Canada.
Trends Cogn Sci. 2014 Oct;18(10):497-500. doi: 10.1016/j.tics.2014.06.006. Epub 2014 Jul 4.
Although probabilistic models of cognitive development have become increasingly prevalent, one challenge is to account for how children might cope with a potentially vast number of possible hypotheses. We propose that children might address this problem by 'sampling' hypotheses from a probability distribution. We discuss empirical results demonstrating signatures of sampling, which offer an explanation for the variability of children's responses. The sampling hypothesis provides an algorithmic account of how children might address computationally intractable problems and suggests a way to make sense of their 'noisy' behavior.
尽管认知发展的概率模型已经越来越普及，但一个挑战是要解释儿童如何应对潜在的大量可能的假设。我们提出，儿童可以通过从概率分布中“抽样”假设来解决这个问题。我们讨论了证明抽样特征的实证结果，这些结果为儿童反应的可变性提供了解释。抽样假设为儿童如何解决计算上难以处理的问题提供了一种算法解释，并为理解他们的“嘈杂”行为提供了一种方法。
