Evolutionary consequences of language learning
Linguistics and Philosophy 20 (6):697-719 (1997)
| Abstract | Linguists intuitions about language change can be captured by adynamical systems model derived from the dynamics of language acquisition.Rather than having to posit a separate model for diachronic change, as hassometimes been done by drawing on assumptions from population biology (cf.Cavalli-Sforza and Feldman, 1973; 1981; Kroch, 1990), this new modeldispenses with these independent assumptions by showing how the behavior ofindividual language learners leads to emergent, global populationcharacteristics of linguistic communities over several generations. As thesimplest case, we formalize the example of two grammars and show that eventhis situation leads directly to a nonlinear (quadratic) dynamical system.We study this one parameter model in a variety of situations for differentkinds of acquisition algorithms and maturational times, showing howdifferent learning theories can have very different evolutionaryconsequences. This allows us to formulate an evolutionary criterion for theadequacy of grammatical and learning theories. An application of thecomputational model to the historical loss of Verb Second from Old French toModern French is described showing how otherwise adequate grammaticaltheories might fail the evolutionary criterion. | |||||||||
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W. Garrett Mitchener (2011). A Mathematical Model of Prediction-Driven Instability: How Social Structure Can Drive Language Change. Journal of Logic, Language and Information 20 (3):385-396.
Fiona Cowie (1997). The Logical Problem of Language Acquisition. Synthese 111 (1):17-51.
Christina Behme & H. S. (2008). Language Learning in Infancy: Does the Empirical Evidence Support a Domain Specific Language Acquisition Device? Philosophical Psychology 21 (5):641 – 671.
Heather Bortfeld (2004). Which Came First: Infants Learning Language or Motherese? Behavioral and Brain Sciences 27 (4):505-506.
Nick Chater & Morten H. Christiansen (2010). Language Acquisition Meets Language Evolution. Cognitive Science 34 (7):1131-1157.
Afsaneh Fazly, Afra Alishahi & Suzanne Stevenson (2010). A Probabilistic Computational Model of Cross-Situational Word Learning. Cognitive Science 34 (6):1017-1063.
Jechil S. Sieratzki & Bencie Woll (1998). An Evolutionary Model for the Learning of Language. Behavioral and Brain Sciences 21 (4):530-530.
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