|Appears in Collections:||Literature and Languages Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Word Learning Under Infinite Uncertainty|
Smith, Andrew D M
|Citation:||Blythe R, Smith ADM & Smith K (2016) Word Learning Under Infinite Uncertainty, Cognition, 151, pp. 18-27.|
|Abstract:||Language learners must learn the meanings of many thousands of words, de- spite those words occurring in complex environments in which infinitely many meanings might be inferred by the learner as a word’s true meaning. This problem of infinite referential uncertainty is often attributed to Willard Van Orman Quine. We provide a mathematical formalisation of an ideal cross- situational learner attempting to learn under infinite referential uncertainty, and identify conditions under which word learning is possible. As Quine’s intuitions suggest, learning under infinite uncertainty is in fact possible, pro- vided that learners have some means of ranking candidate word meanings in terms of their plausibility; furthermore, our analysis shows that this rank- ing could in fact be exceedingly weak, implying that constraints which allow learners to infer the plausibility of candidate word meanings could themselves be weak. This approach lifts the burden of explanation from ‘smart’ word learning constraints in learners, and suggests a programme of research into weak, unreliable, probabilistic constraints on the inference of word meaning in real word learners.|
|Rights:||Accepted refereed manuscript of: Blythe R, Smith ADM & Smith K (2016) Word Learning Under Infinite Uncertainty, Cognition, 151, pp. 18-27. DOI: 10.1016/j.cognition.2016.02.017 This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. © 2016, Elsevier. Licensed under the Creative Commons Attribution- NonCommercial-NoDerivatives 4.0 International http://creativecommons.org/licenses/by-nc-nd/4.0/|
|2016_Word learning under infinite uncertainty (1).pdf||1.18 MB||Adobe PDF||View/Open|
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