Department of Psychology, University College LondonDepartment of Psychology, University of Warwick.
Cogn Sci. 2008 Jan 2;32(1):36-67. doi: 10.1080/03640210701801941.
The remarkable successes of the physical sciences have been built on highly general quantitative laws, which serve as the basis for understanding an enormous variety of specific physical systems. How far is it possible to construct universal principles in the cognitive sciences, in terms of which specific aspects of perception, memory, or decision making might be modelled? Following Shepard (e.g., 1987), it is argued that some universal principles may be attainable in cognitive science. Here, 2 examples are proposed: the simplicity principle (which states that the cognitive system prefers patterns that provide simpler explanations of available data); and the scale-invariance principle, which states that many cognitive phenomena are independent of the scale of relevant underlying physical variables, such as time, space, luminance, or sound pressure. This article illustrates how principles may be combined to explain specific cognitive processes by using these principles to derive SIMPLE, a formal model of memory for serial order (Brown, Neath, & Chater, 2007), and briefly mentions some extensions to models of identification and categorization. This article also considers the scope and limitations of universal laws in cognitive science.
物理科学的显著成功建立在高度通用的定量规律之上，这些规律是理解各种具体物理系统的基础。在认知科学中，是否有可能构建出通用的原则，从而可以对感知、记忆或决策等特定方面进行建模？受谢巴德（例如，1987）的启发，有人认为认知科学中可能存在一些通用原则。在这里，提出了两个示例：简单性原则（该原则指出，认知系统更喜欢提供更简单解释可用数据的模式）和尺度不变性原则，该原则指出，许多认知现象与相关潜在物理变量的尺度无关，例如时间、空间、亮度或声压。本文通过使用这些原则来推导出简单记忆的正式模型（布朗、尼思和恰特，2007），说明了如何将原则结合起来解释特定的认知过程，并简要提及了对识别和分类模型的一些扩展。本文还考虑了认知科学中通用定律的范围和局限性。
