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Authoritative: http://dx.doi.org/10.1364/JOSAA.26.001414   (Publisher's PDF... likely be available here.)

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Abstract

The evolution of color categorization is investigated using artificial agent population categorization games, by modeling observer types using Farnsworth-Munsell 100 Hue Test performance to capture human processing constraints on color categorization. Homogeneous populations of both normal and dichromat agents are separately examined. Both types of populations produce near-optimal categorization solutions. While normal observers produce categorization solutions that show rotational invariance, dichromats' solutions show symmetry-breaking features. In particular, it is found that dichromats' local confusion regions tend to repel color category boundaries and that global confusion pairs attract category boundaries. The trade-off between these two mechanisms gives rise to population categorization solutions where color boundaries are anchored to a subset of locations in the stimulus space. A companion paper extends these studies to more realistic, heterogeneous agent populations [J. Opt. Soc. Am. A 26, 1424-1436 (2009)].

@article{jameson09colorCategorizationI,
  author={Kimberly A. Jameson and Natalia L. Komarova},
  title={Evolutionary models of color categorization. I. Population categorization systems based on normal and dichromat observers},
  journal={J. Opt. Soc. Am. A},
  year={2009},
  volume={26},
  number={6},
  pages={1414-1423},
  doi={10.1364/JOSAA.26.001414},
  url={http://www.isrl.uiuc.edu/~amag/langev/paper/jameson09colorCategorizationI.html}
}