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类别学习与注意力分配的原型和范例模型:重新评估

Prototype and exemplar accounts of category learning and attentional allocation: a reassessment.

作者信息

Zaki Safa R, Nosofsky Robert M, Stanton Roger D, Cohen Andrew L

机构信息

Department of Psychology, Williams College, Williamstown, MA 01267, USA.

出版信息

J Exp Psychol Learn Mem Cogn. 2003 Nov;29(6):1160-73. doi: 10.1037/0278-7393.29.6.1160.

Abstract

In a recent article. J. P. Minda and J. D. Smith (2002; see record 2002-00620-002) argued that an exemplar model provided worse quantitative fits than an alternative prototype model to individual subject data from the classic D. L. Medin and M. M. Schaffer (1978) 5/4 categorization paradigm. In addition, they argued that the exemplar model achieved its fits by making untenable assumptions regarding how observers distribute their attention. In this article, we demonstrate that when the models are equated in terms of their response-rule flexibility, the exemplar model provides a substantially better account of the categorization data than does a prototype or mixed model. In addition, we point to shortcomings in the attention-allocation analyses conducted by J. P. Minda and J. D. Smith (2002). When these shortcomings are corrected, we find no evidence that challenges the attention-allocation assumptions of the exemplar model.

摘要

在最近的一篇文章中,J. P. 明达和J. D. 史密斯(2002年;见记录2002 - 00620 - 002)认为,对于经典的D. L. 梅丁和M. M. 谢弗(1978年)5/4分类范式中的个体受试者数据,范例模型提供的定量拟合比替代的原型模型更差。此外,他们认为范例模型通过对观察者如何分配注意力做出站不住脚的假设来实现其拟合。在本文中,我们证明,当模型在其反应规则灵活性方面相等时,范例模型比原型模型或混合模型能更好地解释分类数据。此外,我们指出了J. P. 明达和J. D. 史密斯(2002年)进行的注意力分配分析中的缺点。当这些缺点得到纠正后,我们没有发现任何证据对范例模型的注意力分配假设提出质疑。

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