Characteristic Sets for Polynomial Grammatical Inference
Machine Learning
Inference of Reversible Languages
Journal of the ACM (JACM)
Polynomial-time identification of very simple grammars from positive data
Theoretical Computer Science - Selected papers in honour of Setsuo Arikawa
Reversible automata and induction of the English auxiliary system
ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
A generative constituent-context model for improved grammar induction
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Corpus-based induction of syntactic structure: models of dependency and constituency
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Contrastive estimation: training log-linear models on unlabeled data
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Identification in the limit of substitutable context-free languages
ALT'05 Proceedings of the 16th international conference on Algorithmic Learning Theory
A linguistic investigation into unsupervised DOP
CACLA '07 Proceedings of the Workshop on Cognitive Aspects of Computational Language Acquisition
Empiricist solutions to nativist puzzles by means of unsupervised TSG
Proceedings of the Workshop on Computational Models of Language Acquisition and Loss
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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.