Proceedings of the Annual Meeting of the Cognitive Science Society

We present new results of a novel computational approach to the interaction of two important cognitive-linguistic phenomena: (1) language learning, long regarded as central to modem synchronic linguistics; and (2) language change over time, diachronic linguistics. We exploit the insight that while language learning takes place at the level of the individual, language change is more properly regarded as an ensemble property that takes place at the level of populations of language learners — while the former has been the subject of much explicit computer modeling, the latter been less extensively treated. We show by analytical and computer simulation methods that language learning can be regarded as the driving force behind a dynamical systems account of language change. We apply this model to the specific (and cognitively relevant) case of the historical change from Classical Portuguese (CP) to European Portuguese (EP). demonstrating how a particular language learning model (for instance, a maximum-likelihood model akin to many statistically-based language approaches), coupled with data on the differences between CP and EP, leads to specific predictions for possible language-change envelopes, as well as delimiting the class of possible language-learning mechanisms and linguistic theories compatible with a given class of changes. The main investigative message of this paper is to show how this methodology can be applied to a specific case, that of Portuguese. The main moral underscores the individual/population difference, and demonstrates the potential subtlety of language change: we show that simply because an individual child will, with high probability, choose a particular grammar (European Portuguese) does not mean that all other grammars (e.g.. Classical Portuguese) will come to be eliminated; rather, contrary to surface intuition, that is property of the dynamical system and the population ensemble itself.