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Bridging levels of analysis for probabilistic models of cognition
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Griffiths, T. L., Vul, E. and Sanborn, Adam N. (2012) Bridging levels of analysis for probabilistic models of cognition. Current Directions in Psychological Science, Volume 21 (Number 4). pp. 263-268. doi:10.1177/0963721412447619
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Official URL: http://dx.doi.org/10.1177/0963721412447619
Abstract
Probabilistic models of cognition characterize the abstract computational problems underlying inductive inferences and identify their ideal solutions. This approach differs from traditional methods of investigating human cognition, which focus on identifying the cognitive or neural processes that underlie behavior and therefore concern alternative levels of analysis. To evaluate the theoretical implications of probabilistic models and increase their predictive power, we must understand the relationships between theories at these different levels of analysis. One strategy for bridging levels of analysis is to explore cognitive processes that have a direct link to probabilistic inference. Recent research employing this strategy has focused on the possibility that the Monte Carlo principle—which concerns sampling from probability distributions in order to perform computations—provides a way to link probabilistic models of cognition to more concrete cognitive and neural processes.
| Item Type: | Journal Article | ||||
|---|---|---|---|---|---|
| Divisions: | Faculty of Science > Psychology | ||||
| Journal or Publication Title: | Current Directions in Psychological Science | ||||
| Publisher: | Sage Publications Ltd. | ||||
| ISSN: | 0963-7214 | ||||
| Official Date: | August 2012 | ||||
| Dates: |
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| Volume: | Volume 21 | ||||
| Number: | Number 4 | ||||
| Page Range: | pp. 263-268 | ||||
| DOI: | 10.1177/0963721412447619 | ||||
| Status: | Peer Reviewed | ||||
| Publication Status: | Published | ||||
| Access rights to Published version: | Restricted or Subscription Access | ||||
| Funder: | National Science Foundation (NSF), Air Force Office of Scientific Research (AFOSR), Office of Naval Research (ONR) | ||||
| Grant number: | IIS-1018733 (NSF); FA-9550- 10-1-0232 (AFOSR); N00014-07-1-0937 (ONR) |
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