CUNY-CoLAG develops and evaluates computational models of syntax acquisition.

We focus on variants of Structural Triggers Learners but are also interested in other principle and parameters learners, extended phrase structure grammars, stochastic grammar learning, artificial neural networks, grammar induction and formal learnability.

We have created a systematic artificial language domain of over 3,000 abstract languages. It involves a broad range of syntactic phenomena typical of child-directed speech: null subjects, subject-aux inversion, negative, interrogative and imperative structures, wh-movement and so on. Click here for more information on our language database.

Information about the Psychocomputational Models of Human Language Acquisition (PsychoCompLA) Workshop series is here: