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Abstract

This paper argues that developmental patterns in child language be taken seriously in computational models of language acquisition, and proposes a formal theory that meets this criterion. We first present developmental facts that are problematic for statistical learning approaches which assume no prior knowledge of grammar, and for traditional learnability models which assume the learner moves from one UG-defined grammar to another. In contrast, we view language acquisition as a population of grammars associated with 'weights', that compete in a Darwinian selectionist process. Selection is made possible by the variational properties of individual grammars; specifically, their differential compatibility with the primary linguistic data in the environment. In addition to a convergence proof, we present empirical evidence in child language development, that a learner is best modeled as multiple grammars in co-existence and competition.

@inproceedings{yang99ACL,
  author={C.D. Yang},
  title={A selectionist theory of language development},
  year={1999},
  pages={429-435},
  address={East Stroudsburg, PA},
  publisher={Association for Computational Linguistics},
  booktitle={Proceedings of 37th Meeting of the Association for Computational Linguistics},
  url={http://www.isrl.uiuc.edu/~amag/langev/paper/yang99ACL.html}
}

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