Language Evolution and Computation Bibliography

Linguistic meaning is a convention. This article investigates how such conventions can arise for color categories in populations of simulated 'agents'. The method uses concepts from evolutionary game theory: A language game where agents assign names to color patches and is played repeatedly by members of a population. The evolutionary dynamics employed make minimal assumptions about agents' perceptions and learning processes. Through various simulations it is shown that under different kinds of reasonable conditions involving outcomes of individual games, the evolutionary dynamics push populations to stationary equilibria, which can be interpreted as achieving shared population meaning systems. Optimal population agreement for meaning is characterized through a mathematical formula, and the simulations presented reveal that for a wide variety of situations, optimality is achieved.

Specifying the factors that contribute to the universality of color categorization across individuals and cultures is a longstanding and still controversial issue in psychology, linguistics, and anthropology. The present article approaches this issue through the simulated evolution of color lexicons. It is shown that the combination of a minimal perceptual psychology of discrimination, simple pragmatic constraints involving communication, and simple learning rules are enough to evolve color naming systems. Implications of this result for psychological theories of color categorization and the evolution of color naming systems in human societies are discussed.