Proceedings of the Annual Meeting of the Cognitive Science Society

The dynamics of language evolution and learning in individuals have been extensively studied. Our knowledge ofthe transmission process in particular has been advanced by the iterated learning model. Additionally, work has been done inthe area of population structure and social networks. However, less has been described about the interaction between individual-level transmission and network structures. We present a general framework for representing transmission and learning algo-rithms within social networks. We demonstrate that population structure interacts with the transmission process to influencethe dynamics of change. Taking network effects into account, studies on language evolution will capture a fuller picture of thephenomenon.