A Computational Account of the Development of the Generalization of Shape Information
A Computational Account of the Development of the Generalization of Shape Information
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DOI：
10.1111/j.1551-6709.2010.01103.x
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发表时间：
2010-05-01
影响因子：
2.5
通讯作者：
Hummel, John E.
中科院分区：
文献类型：
--
作者：
Doumas, Leonidas A. A.;Hummel, John E.
Abechte、Sera、Yonas和Schwade（2001）的研究表明，与年龄较大的儿童和成人相比，幼儿对形状的表征更有度量，也许更全面。一个孩子是如何从把物体和事件当作无差别的整体来表现，转变为用它们的属性来明确地表现它们的？根据RBC（由组件表示理论; Biederman，1987），对象被表示为类别几何部分（“geons”）的集合，特别是类别空间关系。我们建议，从整体到更分类的视觉形状处理的过渡是一个功能的发展geon样表示通过一个过程中的渐进的交叉发现。我们用DORA（Doumas，Hummel，& Sandhofer，2008）来描述这种转变，DORA是一种发现关系概念的模型。我们证明了DORA可以通过比较由多个geon组成的对象来学习单个geon的表示。此外，随着DORA的学习，它遵循与儿童相同的表现轨迹，最初更度量/整体地概括形状，最终分类概括。
Abecassis, Sera, Yonas, and Schwade (2001) showed that young children represent shapes more metrically, and perhaps more holistically, than do older children and adults. How does a child transition from representing objects and events as undifferentiated wholes to representing them explicitly in terms of their attributes? According to RBC (Recognition-by-Components theory; Biederman, 1987), objects are represented as collections of categorical geometric parts ("geons") in particular categorical spatial relations. We propose that the transition from holistic to more categorical visual shape processing is a function of the development of geon-like representations via a process of progressive intersection discovery. We present an account of this transition in terms of DORA (Doumas, Hummel, & Sandhofer, 2008), a model of the discovery of relational concepts. We demonstrate that DORA can learn representations of single geons by comparing objects composed of multiple geons. In addition, as DORA is learning it follows the same performance trajectory as children, originally generalizing shape more metrically/holistically and eventually generalizing categorically.