Predicting focal colors with a rational model of representativeness

Joshua T. Abbott, Terry Regier, Thomas L. Griffiths

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Scopus citations

Abstract

Best examples of categories lie at the heart of two major debates in cognitive science, one concerning universal focal colors across languages, and the other concerning the role of representativeness in inference. Here we link these two debates. We show that best examples of named color categories across 110 languages are well-predicted by a rational model of representativeness, and that this model outperforms several natural competitors. We conclude that categorization in the contested semantic domain of color may be governed by general principles that apply more broadly in cognition, and that these principles clarify the interplay of universal and language-specific forces in color naming.

Original languageEnglish (US)
Title of host publicationBuilding Bridges Across Cognitive Sciences Around the World - Proceedings of the 34th Annual Meeting of the Cognitive Science Society, CogSci 2012
EditorsNaomi Miyake, David Peebles, Richard P. Cooper
PublisherThe Cognitive Science Society
Pages60-65
Number of pages6
ISBN (Electronic)9780976831884
StatePublished - 2012
Externally publishedYes
Event34th Annual Meeting of the Cognitive Science Society: Building Bridges Across Cognitive Sciences Around the World, CogSci 2012 - Sapporo, Japan
Duration: Aug 1 2012Aug 4 2012

Publication series

NameBuilding Bridges Across Cognitive Sciences Around the World - Proceedings of the 34th Annual Meeting of the Cognitive Science Society, CogSci 2012

Conference

Conference34th Annual Meeting of the Cognitive Science Society: Building Bridges Across Cognitive Sciences Around the World, CogSci 2012
Country/TerritoryJapan
CitySapporo
Period8/1/128/4/12

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Science Applications
  • Human-Computer Interaction
  • Cognitive Neuroscience

Keywords

  • Bayesian inference
  • Language and perception
  • color naming
  • representativeness
  • semantic universals

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