Perfors, Amy, Tenenbaum, Joshua B. and Wonnacott, Elizabeth (2010) Variability, negative evidence, and the acquisition of verb argument constructions. Journal of Child Language, Volume 37 (Number 3). pp. 607-642. doi:10.1017/S0305000910000012

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Abstract

We present a hierarchical Bayesian framework for modeling the acquisition of verb argument constructions. It embodies a domain-general approach to learning higher-level knowledge in the form of inductive constraints (or overhypotheses), and has been used to explain other aspects of language development such as the shape bias in learning object names. Here, we demonstrate that the same model captures several phenomena in the acquisition of verb constructions. Our model, like adults in a series of artificial language learning experiments, makes inferences about the distributional statistics of verbs on several levels of abstraction simultaneously. It also produces the qualitative learning patterns displayed by children over the time course of acquisition. These results suggest that the patterns of generalization observed in both children and adults could emerge from basic assumptions about the nature of learning. They also provide an example of a broad class of computational approaches that can resolve Baker's Paradox.

Item Type:	Journal Article
Subjects:	B Philosophy. Psychology. Religion > BF Psychology P Language and Literature > P Philology. Linguistics
Divisions:	Faculty of Science > Psychology
Library of Congress Subject Headings (LCSH):	Language acquisition, Grammar, Comparative and general , Language and languages -- Grammars, Language acquisition -- Research, Bayesian statistical decision theory
Journal or Publication Title:	Journal of Child Language
Publisher:	Cambridge University Press
ISSN:	0305-0009
Official Date:	2010
Dates:	Date Event 2010 Published
Date of first compliant deposit:	23 December 2015
Volume:	Volume 37
Number:	Number 3
Page Range:	pp. 607-642
DOI:	10.1017/S0305000910000012
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Restricted or Subscription Access
Funder:	National Defense Science & Engineering Graduate Fellowships (NDSEG), National Science Foundation (U.S.) (NSF), Paul E. Newton Career Development Chair (PENCDC), James S Mcdonnell Foundation Causal Learning Collaborative Initiative, United States. Air Force. Office of Scientific Research
Grant number:	FA9550-1-0075

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