Why Language Learning Requires Miscalibration

Abstract: As children learn language, they try to mimic adult speech, while leaving room for change. Furthermore, manuscript data shows that language is fuzzy, in that speakers use alternative forms to express the same meaning and that the frequency with which they use those alternatives varies. Thus, child language acquisition requires children to learn usage frequencies for various constructions, as well as which constructions are possible. I will present an ODE model, a more complicated PDE model, and a detailed discrete simulation that all show that children cannot be accurate in replicating the usage frequencies of the adult population. If they are, then the population tends to an incoherent mixture of all possible constructions rather than a single language dominated by one alternative. Instead, children must use a learning algorithm that is miscalibrated so as to prefer usage frequencies close to 0 or 1. With proper miscalibration, the population can settle on a dominant language.