4.1 Article

'Ideal learning' of natural language:: Positive results about learning from positive evidence

Journal

JOURNAL OF MATHEMATICAL PSYCHOLOGY
Volume 51, Issue 3, Pages 135-163

Publisher

ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.jmp.2006.10.002

Keywords

learnability; language acquisition; algorithmic complexity; Kolmogorov; identification in the limit; formal languages

Funding

  1. Economic and Social Research Council [RES-538-28-1001] Funding Source: researchfish

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Gold's [1967. Language identification in the limit. Information and Control, 16, 447-474] celebrated work on learning in the limit has been taken, by many cognitive scientists, to have powerful negative implications for the learnability of language from positive data (i.e., from mere exposure to linguistic input). This provides one, of several, lines of argument that language acquisition must draw on other sources of information, including innate constraints on learning. We consider an 'ideal learner' that applies a Simplicity Principle to the problem of language acquisition. The Simplicity Principle chooses the hypothesis that provides the briefest representation of the available data-here, the data are the linguistic input to the child. The Simplicity Principle allows learning from positive evidence alone, given quite weak assumptions, in apparent contrast to results on language learnability in the limit (e.g., Gold, 1967). These results provide a framework for reconsidering the learnability of various aspects of natural language from positive evidence, which has been at the center of theoretical debate in research on language acquisition and linguistics. (c) 2006 Elsevier Inc. All rights reserved.

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