Skip to main content
SpringerLink
Log in

Bayesian Approaches to Color Category Learning

  • Living reference work entry
  • Latest version View entry history
  • First Online:
Encyclopedia of Color Science and Technology

  • 44 Accesses

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution

Institutional subscriptions

References

  1. Kay, P., Maffi, L.: Color appearance and the emergence and evolution of basic color lexicons. Am. Anthropol. 101(4), 743–760 (1999)

    Article  Google Scholar 

  2. Kay, P., Berlin, B., Maffi, L., Merrifield, W.R., Cook, R.: The World Color Survey. Center for the Study of Language and Information, Stanford (2009)

    Google Scholar 

  3. Kersten, D., Mamassian, P., Yuille, A.: Object perception as Bayesian inference. Annu. Rev. Psychol. 55(1), 271–304 (2004). https://doi.org/10.1146/annurev.psych.55.090902.142005

    Article  Google Scholar 

  4. Tenenbaum, J.B., Kemp, C., Griffiths, T.L., Goodman, N.D.: How to grow a mind: Statistics, structure, and abstraction. Science. 331(6022), 1279–1285 (2011). https://doi.org/10.1126/science.1192788

    Article  ADS  MathSciNet  MATH  Google Scholar 

  5. Tenenbaum, J.B., Griffiths, T.L.: Generalization, similarity, and Bayesian inference. Behav. Brain Sci. 24(4), 629–640 (2001). https://doi.org/10.1017/S0140525X01000061

    Article  Google Scholar 

  6. Xu, F., Tenenbaum, J.B.: Word learning as Bayesian inference. Psychol. Rev. 114(2), 245–272 (2007). https://doi.org/10.1037/0033-295X.114.2.245

    Article  Google Scholar 

  7. Dowman, M.: Explaining color term typology with an evolutionary model. Cogn. Sci. 31(1), 99–132 (2007). https://doi.org/10.1080/03640210709336986

    Article  Google Scholar 

  8. Jones, C.D., Osorio, D., Baddeley, R.J.: Colour categorization by domestic chicks. Proc. R. Soc. Lond. Ser. B Biol. Sci. 268(1481), 2077–2084 (2001). https://doi.org/10.1098/rspb.2001.1734

    Article  Google Scholar 

  9. Kirby, S.: Spontaneous evolution of linguistic structure: An iterated learning model of the emergence of regularity and irregularity. IEEE Trans. Evol. Comput. 5(2), 102–110 (2001)

    Article  Google Scholar 

  10. Griffiths, T.L., Kalish, M.L.: Language evolution by iterated learning with Bayesian agents. Cogn. Sci. 31(3), 441–480 (2007). https://doi.org/10.1080/15326900701326576

    Article  Google Scholar 

  11. Xu, J., Dowman, M., Griffiths, T.L.: Cultural transmission results in convergence towards colour term universals. Proc. Roy. Soc. B: Biol. Sci. 280(1758), 20123073 (2013). https://doi.org/10.1098/rspb.2012.3073

    Article  Google Scholar 

  12. Carstensen, A., Xu, J., Smith, C., Regier, T.: Language evolution in the lab tends toward informative communication. In: Noelle, D.C., Dale, R., Warlaumont, A.S., Yoshimi, J., Matlock, T., Jennings, C.D., Maglio, P.P. (eds.) Proceedings of the 37th annual meeting of the Cognitive Science Society. Cognitive Science Society, Austin (2015)

    Google Scholar 

  13. Carr, J.W., Smith, K., Culbertson, J., Kirby, S.: Simplicity and informativeness in semantic category systems. Cognition. 202, 104289 (2020). https://doi.org/10.1016/j.cognition.2020.104289

    Article  Google Scholar 

  14. Tamariz, M.: Experimental studies on the cultural evolution of language. Ann. Rev. Linguist. 3(1), 389–407 (2017). https://doi.org/10.1146/annurev-linguistics-011516-033807

    Article  Google Scholar 

  15. Zaslavsky, N., Kemp, C., Regier, T., Tishby, N.: Efficient compression in color naming and its evolution. Proc. Natl. Acad. Sci. 115(31), 7937–7942 (2018). https://doi.org/10.1073/pnas.1800521115

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Departments of Psychology and Computer Science, Princeton University, Princeton, NJ, USA

    Thomas L. Griffiths

  2. Department of Brain and Cognitive Sciences and Center for Brains Minds and Machines, MIT, Cambridge, MA, USA

    Noga Zaslavsky

Authors
  1. Thomas L. Griffiths
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Noga Zaslavsky
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Noga Zaslavsky .

Editor information

Editors and Affiliations

  1. Color Science & Imaging Lab, North Carolina State Univ, Raleigh, NC, USA

    Renzo Shamey

Section Editor information

  1. Faculty of Engineering Sciences, University College London, London, Please select, UK

    Lindsay MacDonald

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Science+Business Media LLC

About this entry

Check for updates. Verify currency and authenticity via CrossMark

Cite this entry

Griffiths, T.L., Zaslavsky, N. (2021). Bayesian Approaches to Color Category Learning. In: Shamey, R. (eds) Encyclopedia of Color Science and Technology. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27851-8_60-9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-27851-8_60-9

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-27851-8

  • Online ISBN: 978-3-642-27851-8

  • eBook Packages: Springer Reference Physics and AstronomyReference Module Physical and Materials ScienceReference Module Chemistry, Materials and Physics

Publish with us

Policies and ethics

Chapter history

  1. Latest

    Bayesian Approaches to Color Category Learning
    Published:
    01 January 2021

    DOI: https://doi.org/10.1007/978-3-642-27851-8_60-9

  2. Original

    Bayesian Approaches to Color Category Learning
    Published:
    02 July 2015

    DOI: https://doi.org/10.1007/978-3-642-27851-8_60-8

Search

Navigation