  There is much debate over the degree to which language learning is governed
by innate language-specific biases, or acquired through cognition-general
principles. Here we examine the probabilistic language acquisition hypothesis
on three levels: We outline a novel theoretical result showing that it is
possible to learn the exact generative model underlying a wide class of
languages, purely from observing samples of the language. We then describe a
recently proposed practical framework, which quantifies natural language
learnability, allowing specific learnability predictions to be made for the
first time. In previous work, this framework was used to make learnability
predictions for a wide variety of linguistic constructions, for which
learnability has been much debated. Here, we present a new experiment which
tests these learnability predictions. We find that our experimental results
support the possibility that these linguistic constructions are acquired
probabilistically from cognition-general principles.
