Language is a complex adaptive system: Speakers are agents who interact with each other, and their past and current interactions feed into speakers' future behavior in complex ways. In this article, we describe the social cognitive linguistic basis for this analysis of language and a mathematical model developed in collaboration between researchers in linguistics and statistical physics. The model has led us to posit two mechanisms of selection--neutral interactor selection and weighted interactor selection--in addition to neutral evolution and replicator selection (fitness). We describe current results in modeling language change in terms of neutral interactor selection and weighted interactor selection.