Language Evolution and Computation Bibliography

This paper contrasts two influential theoretical accounts of language change and evolution a Iterated Learning and Social Coordination. The contrast is based on an experiment that compares drawings produced with Garrod et alas (2007) apictionarya task with those produced in an Iterated Learning version of the same task. The main finding is that Iterated Learning does not lead to the systematic simplification and increased symbolicity of graphical signs produced in the standard interactive version of the task. A second finding is that Iterated Learning leads to less conceptual and structural alignment between participants than observed for those in the interactive condition. The paper concludes with a comparison of the two accounts in relation to how each promotes signs that are effi cient, systematic and learnable.

Imitation alone cannot explain language evolution. Two additional ingredients have been proposed that may help explain the evolution of language systems: learning biases and social collaboration. An experimental method was developed that isolated the roles of collaboration and learning biases in the development of novel communication systems. Participants played a Pictionary-like task to develop ad hoc graphical communication systems in one of two conditions: one in which they interacted with a partner (Interaction condition), and one in which they received the same images from a apseudo-partnera but did not interact (Pseudo-Interaction condition). Comparison of the resultant communication systems showed that the Interaction condition yielded higher identification accuracy, greater refinement of graphical signs and more alignment on a set of shared graphical signs (in fact, graphical alignment did not occur at all in the Pseudo-Interaction condition). Thus, collaboration plays a crucial role in the evolution of human communication systems.