A Mathematical Model of Prediction-Driven Instability: How
Social Structure Can Drive Language Change Journal of Logic,
Language and Information 20 (3):385-396 (2011) |Abstract||I
discuss a stochastic model of language learning and change.
During a syntactic change, each speaker makes use of
constructions from two different idealized grammars at variable
rates. The model incorporates regularization in that speakers
have a slight preference for using the dominant idealized
grammar. It also includes incrementation: The population is
divided into two interacting generations. Children can detect
correlations between age and speech. They then predict where the
population’s language is moving and speak according to that
prediction, which represents a social force encouraging children
not to sound out-dated. Both regularization and incrementation
turn out to be necessary for spontaneous language change to
occur on a reasonable time scale and run to completion
monotonically. Chance correlation between age and speech