Hostname: page-component-cd9895bd7-fscjk Total loading time: 0 Render date: 2024-12-23T08:22:46.719Z Has data issue: false hasContentIssue false
  • English
  • Français

Come down from the clouds: Grounding Bayesian insights in developmental and behavioral processes

Published online by Cambridge University Press:  25 August 2011

Gavin W. Jenkins ,
Larissa K. Samuelson  and
John P. Spencer
Gavin W. Jenkins
Affiliation:
Department of Psychology and Delta Center, University of Iowa, Iowa City, IA 52242-1407. [email protected]://www.psychology.uiowa.edu/people/[email protected]://www.psychology.uiowa.edu/people/[email protected]://www.psychology.uiowa.edu/people/john_spencer
Larissa K. Samuelson
Affiliation:
Department of Psychology and Delta Center, University of Iowa, Iowa City, IA 52242-1407. [email protected]://www.psychology.uiowa.edu/people/[email protected]://www.psychology.uiowa.edu/people/[email protected]://www.psychology.uiowa.edu/people/john_spencer
John P. Spencer
Affiliation:
Department of Psychology and Delta Center, University of Iowa, Iowa City, IA 52242-1407. [email protected]://www.psychology.uiowa.edu/people/[email protected]://www.psychology.uiowa.edu/people/[email protected]://www.psychology.uiowa.edu/people/john_spencer
Get access Rights & Permissions [Opens in a new window]

Abstract

According to Jones & Love (J&L), Bayesian theories are too often isolated from other theories and behavioral processes. Here, we highlight examples of two types of isolation from the field of word learning. Specifically, Bayesian theories ignore emergence, critical to development theory, and have not probed the behavioral details of several key phenomena, such as the “suspicious coincidence” effect.

Type
Open Peer Commentary
Information
Behavioral and Brain Sciences , Volume 34 , Issue 4 , August 2011 , pp. 204 - 206
Copyright
Copyright © Cambridge University Press 2011

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Goldstone, R. (1994) An efficient method for obtaining similarity data. Behavior Research Methods, Instruments, and Computers 26:381–86.CrossRefGoogle Scholar
Jenkins, G. J., Smith, J. R., Spencer, J. P. & Samuelson, L. K. (in press) When more evidence makes word learning less suspicious. In: Proceedings of the 33rd Annual Conference of the Cognitive Science Society, ed. Carlson, L., Hölscher, C., & Shipley, T.. Cognitive Science Society.Google Scholar
Kemp, C., Perfors, A. & Tenenbaum, J. B. (2007) Learning overhypotheses with hierarchical Bayesian models. Developmental Science 10:307–21.CrossRefGoogle ScholarPubMed
Perry, L. K., Cook, S. W. & Samuelson, L. K. (in preparation) An exploration of context, task, and stimuli effects on similarity perception.Google Scholar
Samuelson, L. K., Schutte, A. R. & Horst, J. S. (2009) The dynamic nature of knowledge: Insights from a dynamic field model of children's novel noun generalization. Cognition 110:322–45.CrossRefGoogle ScholarPubMed
Smith, L. B. (2000) Learning how to learn words: An associative crane. In: Becoming a word learner: A debate on lexical acquisition, ed. Golinkoff, R. M., Hirsh-Pasek, K., Bloom, L., Smith, L.B., Woodward, A. L., Akhtar, N., Tomasello, M. & Hollich, G., pp. 51–80. Oxford University Press.CrossRefGoogle Scholar
Smith, L. B., Jones, S. S., Landau, B., Gershkoff-Stowe, L. & Samuelson, L. (2002) Object name learning provides on-the-job training for attention. Psychological Science 13:13–19.CrossRefGoogle ScholarPubMed
Smith, L. B. & Thelen, E. (2003) Development as a dynamic system. Trends in Cognitive Science 7(8):343–48.CrossRefGoogle ScholarPubMed
Spencer, J. P. & Perone, S. (2008) Defending qualitative change: The view from dynamical systems theory. Child Development 79:1639–47.CrossRefGoogle ScholarPubMed
Spencer, J. P., Perone, S., Smith, L. B. & Samuelson, L. K. (2011) The process behind the “suspicious coincidence”: Using space and time to learn words. Psychological Science. doi: 10.1177/0956797611413934 CrossRefGoogle ScholarPubMed
Spencer, J. P., Thomas, M. S. & McClelland, J. L. (2009) Toward a unified theory of development: Connectionism and dynamic systems theory re-considered. Oxford University Press.CrossRefGoogle Scholar
Tenenbaum, J. B., Kemp, C., Griffiths, T. L. & Goodman, N. D. (2011) How to grow a mind: Statistics, structure, and abstraction. Science 331(6022):1279–85.CrossRefGoogle Scholar
Xu, F. & Tenenbaum, J. B. (2007a) Sensitivity to sampling in Bayesian word learning. Developmental Science 10(3):288–97.CrossRefGoogle ScholarPubMed
Xu, F. & Tenenbaum, J. B. (2007b) Word learning as Bayesian inference. Psychological Review 114(2):245–72.CrossRefGoogle ScholarPubMed