The ways in which languages have come to divide the visible spectrum with their color terminology, in both their variety and the apparent universal tendencies, are still largely unexplained. Building on recent work in modeling color perception and categorization, as well as the theory of signaling games, we incrementally construct a color categorization model which combines perceptual characteristics of individual agents, game-theoretic signaling interaction of these agents, and the probability of observing particular colors as an environmental constraint. We also propose a method of transparent evaluation against the data gathered in the World Color Survey. The results show that the model’s predictive power is comparable to the current state of the art. Additionally, we argue that the model we suggest is superior in terms of motivation of the principles involved, and that its explanatory relevance with respect to color categorization in languages is therefore higher. Our results suggest that the universal tendencies of color categorization cannot be explained solely in terms of the shape of the color space induced by our perceptual apparatus. We believe that only by taking the heterogeneity of the phenomenon seriously can we acquire a deeper understanding of why color categorization takes the forms we observe across languages.
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