Learning Auxiliary Fronting with Grammatical Inference

We present a simple context-free grammatical inference algorithm, and prove that it is capable of learning an interesting subclass of context-free languages. We also demonstrate that an implementation of this algorithm is capable of learning auxiliary fronting in polar interrogatives (AFIPI) in English. This has been one of the most important test cases in language acquisition over the last few decades. We demonstrate that learning can proceed even in the complete absence of examples of particular constructions, and thus that debates about the frequency of occurrence of such constructions are irrelevant. We discuss the implications of this on the type of innate learning biases that must be hypothesized to explain first language acquisition.