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基于主体的颜色分类中的群体异质性和颜色刺激异质性。

Population heterogeneity and color stimulus heterogeneity in agent-based color categorization.

作者信息

Komarova Natalia L, Jameson Kimberly A

机构信息

Department of Mathematics, University of California, Irvine, CA, USA.

出版信息

J Theor Biol. 2008 Aug 21;253(4):680-700. doi: 10.1016/j.jtbi.2008.03.030. Epub 2008 Apr 4.

Abstract

Investigating the interactions between universal and culturally specific influences on color categorization across individuals and cultures has proven to be a challenge for human color categorization and naming research. The present article simulates the evolution of color lexicons to evaluate the role of two realistic constraints found in the human phenomenon: (i) heterogeneous observer populations and (ii) heterogeneous color stimuli. Such constraints, idealized and implemented as agent categorization and communication games, produce interesting and unexpected consequences for stable categorization solutions evolved and shared by agent populations. We find that the presence of a small fraction of color deficient agents in a population, or the presence of a "region of increased salience" in the color stimulus space, break rotational symmetry in population categorization solutions, and confine color category boundaries to a subset of available locations. Further, these heterogeneities, each in a different, predictable, way, might lead to a change of category number and size. In addition, the concurrent presence of both types of heterogeneity gives rise to novel constrained solutions which optimize the success rate of categorization and communication games. Implications of these agent-based results for psychological theories of color categorization and the evolution of color naming systems in human societies are discussed.

摘要

研究普遍因素与特定文化因素对不同个体和文化中颜色分类的相互作用,已被证明是人类颜色分类和命名研究中的一项挑战。本文模拟了颜色词汇的演变,以评估人类现象中发现的两个现实约束条件的作用:(i)异质的观察者群体和(ii)异质的颜色刺激。这些约束条件被理想化并作为智能体分类和通信博弈来实现,对智能体群体进化和共享的稳定分类解决方案产生了有趣且意想不到的结果。我们发现,群体中一小部分颜色缺陷智能体的存在,或者颜色刺激空间中“显著度增加区域”的存在,会打破群体分类解决方案中的旋转对称性,并将颜色类别边界限制在可用位置的一个子集内。此外,这些异质性,各自以不同的、可预测的方式,可能导致类别数量和大小的变化。此外,两种类型异质性的同时存在会产生新颖的约束解决方案,从而优化分类和通信博弈的成功率。本文讨论了这些基于智能体的结果对颜色分类心理学理论以及人类社会中颜色命名系统演变的影响。

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