颜色命名模式中普遍性的出现
Modeling the emergence of universality in color naming patterns
摘要：
人类颜色分类在不同文化中表现出一些超越表面差异的普遍模式，这是认知科学的一个重大突破。正如世界色彩调查（WCS）所观察到的那样，任何两组个体确实会发展出完全不同的分类模式，但通过对大量人群进行统计分析，可以识别出一些普遍的属性。在这里，我们重现了WCS在一个数字模型中，不同的人群独立发展自己的分类系统，通过玩小学的语言游戏。我们发现，一个简单的感知约束共享的所有人类，即人类的JND（Just Noticeable Difference），是足以引发普遍模式的出现，不受约束的文化互动未能产生。我们通过执行与量化WCS中所示的普遍趋势相同的统计分析来测试我们针对真实数据的实验结果[Kay P和Regier T。等人（2003）Proc. Acad. Sci. USA 100：9085-9089]，并获得优异的定量一致性。这项工作证实，综合建模现在已经达到成熟，大大有助于正在进行的辩论在认知科学。
英文摘要：
The empirical evidence that human color categorization exhibits some universal patterns beyond superficial discrepancies across different cultures is a major breakthrough in cognitive science. As observed in the World Color Survey (WCS), indeed, any two groups of individuals develop quite different categorization patterns, but some universal properties can be identified by a statistical analysis over a large number of populations. Here, we reproduce the WCS in a numerical model in which different populations develop independently their own categorization systems by playing elementary language games. We find that a simple perceptual constraint shared by all humans, namely the human Just Noticeable Difference (JND), is sufficient to trigger the emergence of universal patterns that unconstrained cultural interaction fails to produce. We test the results of our experiment against real data by performing the same statistical analysis proposed to quantify the universal tendencies shown in the WCS [Kay P and Regier T. (2003) Proc. Natl. Acad. Sci. USA 100: 9085-9089], and obtain an excellent quantitative agreement. This work confirms that synthetic modeling has nowadays reached the maturity to contribute significantly to the ongoing debate in cognitive science.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
