Abstraction in perceptual symbol systems
Abstraction in perceptual symbol systems
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DOI：
10.1098/rstb.2003.1319
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发表时间：
2003-07-29
影响因子：
6.3
通讯作者：
Barsalou, LW
中科院分区：
文献类型：
--
作者：
Barsalou, LW
在回顾了抽象的六种含义之后，本文将重点讨论采用摘要表示形式的抽象。建立了这些抽象的三个中心属性：（i）类型标记解释;（ii）结构化表示;（iii）动态实现。传统的表征理论很好地处理了解释和结构，但不够动态。相反，联结主义理论是动态的，但在结构上有问题。感知符号系统提供了一种自然实现所有三个属性的方法。在这个框架内，开发了一个松散的属性和关系模拟器集合来表示抽象。类型标记解释的结果绑定属性模拟器的感知或模拟类别成员的区域。结构化表示是将属性和关系模拟器的配置以集成的方式绑定到多个区域的结果。动态实现的结果是在不同的场合下将不同的属性和关系模拟器子集应用于类别成员。从这个观点来看，在记忆中没有一个范畴的永久或完全的抽象。相反，抽象是构建类别成员的临时在线解释的技能。虽然抽象的可能性是无限的，但吸引子是为解释的习惯方法而发展的。这种方法为抽象现象的分类、推理、背景知识和学习提供了新的思路。
After reviewing six senses of abstraction, this article focuses on abstractions that take the form of summary representations. Three central properties of these abstractions are established: (i) type-token interpretation; (ii) structured representation; and (iii) dynamic realization. Traditional theories of representation handle interpretation and structure well but are not sufficiently dynamical. Conversely, connectionist theories are exquisitely dynamic but have problems with structure. Perceptual symbol systems offer an approach that implements all three properties naturally. Within this framework, a loose collection of property and relation simulators develops to represent abstractions. Type-token interpretation results from binding a property simulator to a region of a perceived or simulated category member. Structured representation results from binding a configuration of property and relation simulators to multiple regions in an integrated manner. Dynamic realization results from applying different subsets of property and relation simulators to category members on different occasions. From this standpoint, there are no permanent or complete abstractions of a category in memory. Instead, abstraction is the skill to construct temporary online interpretations of a category's members. Although an infinite number of abstractions are possible, attractors develop for habitual approaches to interpretation. This approach provides new ways of thinking about abstraction phenomena in categorization, inference, background knowledge and learning.