Identifying representations of categories of discrete items using Markov chain Monte Carlo with People

Anne S. Hsu, Jay B. Martin, Adam N. Sanborn, Thomas L. Griffiths

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

6 Scopus citations

Abstract

Identifying the structure of mental representations is a basic problem for cognitive science. We present a method for identifying people’s representations of categories that are defined over a set of discrete items, such as a collection of images. This method builds on previous work using Markov chain Monte Carlo algorithms as the basis for designing behavioral experiments, and we thus call it discrete Markov chain Monte Carlo with People (d-MCMCP). We illustrate how this approach can be used to identify the structure of visual categories using real images drawn from large databases.

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
Pages485-490
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

  • Markov chain Monte Carlo
  • category representation
  • image databases

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