分类和类别学习中的单系统和多系统

IF 16.8 Q1 PSYCHOLOGY, MULTIDISCIPLINARY
John Paul Minda, Casey L. Roark, Priya Kalra, Anthony Cruz
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引用次数: 0

摘要

学会对世界进行分类是人类认知的基础。有些分类似乎是根据规则明确进行的,而另一些分类似乎是根据相似性隐含进行的。有几种理论认为,分类涉及多个学习系统,或者分类由一个学习系统完成。多系统方法假设人们通过显性的语言系统和隐性的程序系统来学习新的分类。单系统方法则假定,类别是通过单一的认知系统学习的,该系统依赖于刺激的相似性和选择性注意。在这篇综述中,我们首先概述了分类领域的主要理论和模型,并强调了每种理论和模型的假设和运行特点。然后,我们讨论来自认知心理学、认知神经科学、计算建模和比较心理学的证据,以确定哪种方法最有说服力。我们的结论是,多系统理论和单系统方法之间的争论尚未解决,并提出了未来研究的途径,以创建一个强大的理论,解释实验室之外和分类学习范式范围之外的分类学习。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Single and multiple systems in categorization and category learning

Single and multiple systems in categorization and category learning

Single and multiple systems in categorization and category learning
Learning to classify the world into categories is fundamental to human cognition. Some categorizations seem to be made explicitly based on rules whereas other categorizations seem to be made implicitly based on similarity. Several theories posit either that multiple learning systems are involved in categorization or that categorization is carried out by a single learning system. The multiple-system approach assumes that people learn new categories via an explicit verbal system and an implicit procedural system. The single-system approach assumes that categories are learned by a single cognitive system that relies on stimulus similarity and selective attention. In this Review, we first provide an overview of the primary theories and models in the field of categorization and highlight the assumptions and operating characteristics of each. We then discuss evidence from cognitive psychology, cognitive neuroscience, computational modelling and comparative psychology to determine which approach is best supported. We conclude that the debate between a multiple-system theory and a single-system approach has not yet been resolved and suggest avenues for future research to create a robust theory that accounts for category learning beyond the laboratory and beyond the confines of the classification learning paradigm. Classifying the world into categories is fundamental to human cognition. In this Review, Minda et al. highlight the assumptions and operating characteristics of theories positing multiple versus single category learning systems and detail evidence for each approach.
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CiteScore
9.30
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