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Human communication systems, such as language, evolve culturally; theircomponents undergo reproduction and variation. However, a role for selection incultural evolutionary dynamics is less clear. Often neutral evolution (alsoknown as 'drift') models, are used to explain the evolution of humancommunication systems, and cultural evolution more generally. Under thisaccount, cultural change is unbiased: for instance, vocabulary, baby names andpottery designs have been found to spread through random copying.  While drift is the null hypothesis for models of cultural evolution it doesnot always adequately explain empirical results. Alternative models includecultural selection, which assumes variant adoption is biased. Theoreticalmodels of human communication argue that during conversation interlocutors arebiased to adopt the same labels and other aspects of linguistic representation(including prosody and syntax). This basic alignment mechanism has beenextended by computer simulation to account for the emergence of linguisticconventions. When agents are biased to match the linguistic behavior of theirinterlocutor, a single variant can propagate across an entire population ofinteracting computer agents. This behavior-matching account operates at thelevel of the individual. We call it the Conformity-biased model. Under adifferent selection account, called content-biased selection, functionalselection or replicator selection, variant adoption depends upon the intrinsicvalue of the particular variant (e.g., ease of learning or use). This secondalternative account operates at the level of the cultural variant. FollowingBoyd and Richerson we call it the Content-biased model. The present paper teststhe drift model and the two biased selection models' ability to explain thespread of communicative signal variants in an experimental micro-society.

Human Communication Systems Evolve by Cultural Selection