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dc.contributor.authorGibson, Edward A
dc.contributor.authorFutrell, Richard
dc.contributor.authorPiantadosi, Steven
dc.contributor.authorDautriche, Isabelle
dc.contributor.authorMahowald, Kyle
dc.contributor.authorBergen, Leon
dc.contributor.authorLevy, Roger Philip
dc.contributor.authorLevy, Roger P
dc.date.accessioned2019-11-15T19:54:26Z
dc.date.available2019-11-15T19:54:26Z
dc.date.issued2019-02
dc.identifier.urihttps://hdl.handle.net/1721.1/122958
dc.description.abstractCognitive science applies diverse tools and perspectives to study human language. Recently, an exciting body of work has examined linguistic phenomena through the lens of efficiency in usage: what otherwise puzzling features of language find explanation in formal accounts of how language might be optimized for communication and learning? Here, we review studies that deploy formal tools from probability and information theory to understand how and why language works the way that it does, focusing on phenomena ranging from the lexicon through syntax. These studies show how apervasive pressure for efficiency guides the forms of natural language and indicate that a rich future for language research lies in connecting linguistics to cognitive psychology and mathematical theories of communication and inference. Keywords: communication; cross-linguistic universals; language complexity; language efficiency; language evolution; language learnabilityen_US
dc.publisherCenter for Open Scienceen_US
dc.relation.isversionofhttp://dx.doi.org/10.31234/osf.io/w5m38en_US
dc.rightsCreative Commons Attribution-NonCommercial-NoDerivs Licenseen_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_US
dc.sourceProf. Levy via Courtney Crummetten_US
dc.titleHow Efficiency Shapes Human Languageen_US
dc.title.alternativeHow Efficiency Shapes Human Language, TICS 2019en_US
dc.typeArticleen_US
dc.identifier.citationGibson, Edward, et al. “How Efficiency Shapes Human Language, TICS 2019.” PsyArXiv, 23 Feb. 2019. Web.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciences
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dspace.date.submission2019-11-06T16:22:12Z


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