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Baronchelli, A.; Gong, T.; Puglisi, A.; Loreto, V. (2010)
Publisher: National Academy of Sciences
Languages: English
Types: Article
Subjects: Computer Science - Multiagent Systems, Color, Quantitative Biology - Populations and Evolution, Physics - Physics and Society, Cross-Cultural Comparison, Multiagent modeling, Language, Models, Biological, Color Perception - Physiology, Computational cognitive science, Statistical physics, QC, Complex systems, Social Sciences, Computer Science - Computer Science and Game Theory, Natural categorization, Condensed Matter - Statistical Mechanics, Humans
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.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

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    • 0.25 0.5 stimulus 0.75 1.05 1.1 1.15 normalized Dispersion 1.2
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