2009/08/31 by Andrea Baronchelli, Tao Gong, Andrea Puglisi +1 · 176 citations
Biochemistry, Genetics and Molecular Biology · Computer Science · Mathematics · Physics and Astronomy · Psychology · #Artificial intelligence #Categorization #Categorization, perception, and language #Cognition #Cognitive psychology #Computer science #Constraint (computer-aided design) #Mathematics #Natural language processing #Perception #Psychology #Universality (dynamical systems) #cond-mat.stat-mech #cs.GT #cs.MA #physics.soc-ph #q-bio.PE
paper · pdf · doi:10.1073/pnas.0908533107
published in Proceedings of the National Academy of Sciences 107(6), 2403-2407 (National Academy of Sciences) · Supplementery Information available here http://www.pnas.org/content/107/6/2403/suppl/DCSupplemental
openalex publication_date 2010/01/25 · arxiv created 2010/07/08 · arxiv updated 2010/07/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/05
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.