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Abstract:
This article briefly reviews some recent work on artificial language learning in children
and adults. The final part of the article is devoted to a theoretical formulation of
the language learning problem from a mechanistic neurobiological viewpoint and we
show that it is logically possible to combine the notion of innate language constraints
with, for example, the notion of domain general learning mechanisms. A growing body of empirical evidence suggests that the mechanisms involved in artificial language learning and in structured sequence processing are shared with those of natural language
acquisition and natural language processing. Finally, by theoretically analyzing a formal learning model, we highlight Fodor’s insight that it is logically possible to combine innate, domain-specific constraints with domain-general learning mechanisms.
