期刊
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
卷 107, 期 6, 页码 2403-2407出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.0908533107
关键词
computational cognitive science; natural categorization; multiagent modeling; complex systems; statistical physics
资金
- European Social Fund
- Fondo Europeo de Desarrollo Regional [FIS2007-66485-C02-01]
- Alexander von Humboldt Foundation in Germany
- Italian MIUR under the FIRB-IDEAS [RBID08Z9JE]
- European Commission [IST-34721, 043415]
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 & 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.
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