title: Language learning from positive evidence, reconsidered: a simplicity-based approach.
abstract: Children learn their native language by exposure to their linguistic and communicative environment, but apparently without requiring that their mistakes be corrected. Such learning from "positive evidence" has been viewed as raising "logical" problems for language acquisition. In particular, without correction, how is the child to recover from conjecturing an over-general grammar, which will be consistent with any sentence that the child hears? There have been many proposals concerning how this "logical problem" can be dissolved. In this study, we review recent formal results showing that the learner has sufficient data to learn successfully from positive evidence, if it favors the simplest encoding of the linguistic input. Results include the learnability of linguistic prediction, grammaticality judgments, language production, and form-meaning mappings. The simplicity approach can also be "scaled down" to analyze the learnability of specific linguistic constructions, and it is amenable to empirical testing as a framework for describing human language acquisition.
authors: Department of Cognitive, Perceptual and Brain Sciences, University College London, UK. anne.hsu@ ucl.ac.uk
authors: Anne S
authors: AS
authors: Hsu
authors: Nick
authors: N
authors: Chater
authors: Paul
authors: P
authors: Vitányi
mesh_terms: D001499:Bayes Theorem; D005793:Generalization, Psychological; D006801:Humans; D007257:Information Theory; D007804:Language Development; D007858:Learning / Q000502:physiology*; D008037:Linguistics / Q000706:statistics & numerical data*; D015233:Models, Statistical; D011337:Probability Learning