Suppr超能文献

一种关于关系概念的发现与预测的理论。

A theory of the discovery and predication of relational concepts.

作者信息

Doumas Leonidas A A, Hummel John E, Sandhofer Catherine M

机构信息

Department of Psychology, Indiana University, Bloomington 47405, USA.

出版信息

Psychol Rev. 2008 Jan;115(1):1-43. doi: 10.1037/0033-295X.115.1.1.

Abstract

Relational thinking plays a central role in human cognition. However, it is not known how children and adults acquire relational concepts and come to represent them in a form that is useful for the purposes of relational thinking (i.e., as structures that can be dynamically bound to arguments). The authors present a theory of how a psychologically and neurally plausible cognitive architecture can discover relational concepts from examples and represent them as explicit structures (predicates) that can take arguments (i.e., predicate them). The theory is instantiated as a computer program called DORA (Discovery Of Relations by Analogy). DORA is used to simulate the discovery of novel properties and relations, as well as a body of empirical phenomena from the domain of relational learning and the development of relational representations in children and adults.

摘要

关系性思维在人类认知中起着核心作用。然而,目前尚不清楚儿童和成人是如何习得关系性概念,并以一种对关系性思维有用的形式来表征它们的(即作为可以动态绑定到论据的结构)。作者提出了一种理论,阐述了一种在心理学和神经学上合理的认知架构如何能够从示例中发现关系性概念,并将它们表征为可以接受论据的显式结构(谓词)(即对它们进行谓述)。该理论被实例化为一个名为DORA(通过类比发现关系)的计算机程序。DORA被用于模拟新属性和关系的发现,以及来自关系学习领域的一系列实证现象,以及儿童和成人关系表征的发展。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验