The Evolution of Shared Concepts in Changing Populations
The evolution of color categorization systems is investigated by simulating categorization games played by a population of artificial agents. The constraints placed on individual agent’s perception and cognition are minimal and involve limited color discriminability and learning through reinforcement. The main dynamic mechanism for population evolution is pragmatic in nature: There is a pragmatic need for communication between agents, and if the results of such communications have positive consequences in their shared world then the agents involved are positively rewarded, whereas if the results have negative consequences, then involved agents are punished. A mechanism for changing the composition of the population due to agents’ birth and death is also investigated. This birth-death mechanism is found to effectively move an established population color naming system toward a theoretically more optimal one. The simulation results of this article provide insights regarding mechanisms that may constrain universal tendencies in human color categorization systems observed in the linguistic and anthropological literatures.
This research was supported by The National Science Foundation 2014-2018 (#SMA-1416907, K.A. Jameson, PI), and by an award from the University of California Irvine Multidisciplinary Design Program Award to J. Park. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
- Axelrod, R., and R.A. Hammond. 2003. The evolution of ethnocentric behavior. Paper presented at midwest political science convention, Chicago, IL.Google Scholar
- Berlin, B., and P. Kay. 1969. Basic color terms: Their universality and evolution. Berkeley: University of California Press.Google Scholar
- Farnsworth, D. 1949/1957. The Farnsworth-Munsell 100 hue test for the examination of color vision. Baltimore: Munsell Color Company.Google Scholar
- Gladstone, W.E. 1858. Studies on Homer and the Homeric age. I. Oxford: Oxford University Press.Google Scholar
- Gooyabadi, M., and K. Joe. 2018. ColorSims 2.0: an extension to the python package for evolving linguistic color naming conventions applied to a population of agents. IMBS Technical report series, MBS 18-02, Institute for mathematical behavioral sciences.Google Scholar
- Hardin, C.L. 2013. Berlin & Kay theory. Encyclopedia of color science and technology. New York: Springer Science+Business Media.Google Scholar
- Jameson, K., and R.G D’andrade. 1997. It’s not really red, green, yellow, blue: an inquiry into cognitive color space. Color categories in thought and language, eds. Hardin C.L. and Maffi L., 295–318. England, Cambridge University Press.Google Scholar
- Jameson, K.A., and N.L. Komarova. 2009. Evolutionary models of color categorization. I. Population categorization systems based on normal and dichromat observers. Journal of the Optical Society of America A 26(6): 1414–1423. Reprinted in The Virtual Journal of Biomedical Optics, 4(8).CrossRefGoogle Scholar
- Kay, P., and R. Cook. 2015. World color survey. Encyclopedia of color science and technology, eds. Jameson K. and Ronnier Luo. Berlin, Springer. ISBN: 978-3-642-27851-8. DOI 10.1007/978-3-642-27851-8.Google Scholar
- Kay, P., B. Berlin, L. Maffi, W.R. Merrifield, and R. Cook. 2009. The world color survey. Stanford: CSLI. http://www.icsi.berkeley.edu/wcs/data.html.
- Lewis, D. 1969. Convention. Cambridge: Harvard University Press.Google Scholar
- Maynard Smith, J., and D. Harper. 2003. Animal signals. Oxford: Oxford University Press.Google Scholar
- Mesoudi, A., and A. Whiten. 2008. The multiple roles of cultural transmission experiments in understanding human cultural evolution. Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences 363(1509): 3489–501. https://doi.org/10.1098/rstb.2008.0129.CrossRefGoogle Scholar
- Quine, W.V. 1936. Truth by convention. Philosophical essays for A.N. Whitehead, ed. Lee O.H. New York, Longmans.Google Scholar
- Quine, W.V. 1961. Two dogmas of empiricism. From a logical point of view, ed. W.V. Quine, 20–46. Cambridge, Harvard University Press.Google Scholar
- Quine, W.V. 1963. Carnap and logical truth. The Philosophy of Rudolf Carnap, ed. P.A. Schilipp, 385–406. LaSalle, Open Court.Google Scholar
- Skyrms, B. 2004. The stag hunt and the evolution of social structure. Cambridge: Cambridge University Press.Google Scholar
- Tamariz, M. 2017. Experimental studies on the cultural evolution of language. Annual Review of Linguistics 3(1): 389–407. https://doi.org/10.1146/annurev-linguistics-011516-033807.CrossRefGoogle Scholar
- Tauber, S. 2015. Colorsims: a python package for evolving linguistic color naming conventions within a population of simulated agents. University of California, Irvine. Institute for mathematical behavioral sciences, technical report series. #MBS 15–01.Google Scholar