Language Evolution and Computation Bibliography

Evolutionary game theory is used to form a finite partition of a continuous hue circle in which perceptually similar hues are each represented by an icon chip and the circle by a finite but game dynamically determined number of icon chips. On the basis of such icon chip structures, a color categorization for both an individual learner and a population of learners is then evolved. These results remove limitations of some particular previous color categorization simulation work which assumed a fixed number of color stimuli and a maximal number of predefined color categories. These simulations are extended to demonstrate that learners need neither to share the same icon chip structures, nor do these structures have to be fully developed for a population of learners to produce a stable color categorization system. Additionally, when a naive learner is introduced into a population with a stable color categorization, the game dynamics result in the learner's adopting the existing categorization. All results are shown to hold while the underlying icon chip structures evolve continuously in response to novel stimuli. The usefulness of the approach as well as some of the potential implications of the results for human learning of color categories are discussed.