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To simulate or not? Comment on steingroever, Wetzels, and Wagenmakers (2014)
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Konstantinidis, Emmanouil | - |
dc.contributor.author | Speekenbrink, Maarten | - |
dc.contributor.author | Stout, Julie C. | - |
dc.contributor.author | Ahn, Woo-Young | - |
dc.contributor.author | Shanks, David R. | - |
dc.date.accessioned | 2024-04-24T02:33:57Z | - |
dc.date.available | 2024-04-24T02:33:57Z | - |
dc.date.created | 2024-04-17 | - |
dc.date.created | 2024-04-17 | - |
dc.date.created | 2024-04-17 | - |
dc.date.issued | 2014 | - |
dc.identifier.citation | Decision, Vol.1 No.3, pp.184-191 | - |
dc.identifier.issn | 2325-9965 | - |
dc.identifier.uri | https://hdl.handle.net/10371/199359 | - |
dc.description.abstract | Steingroever, Wetzels, and Wagenmakers (2014) conducted a detailed investigation of 3 popular reinforcement-learning models for the Iowa gambling task using 2 model comparison techniques: a post hoc fit criterion and a simulation method. However, these 2 methods yield inconsistent results regarding which model should be preferred as a description of underlying psychological processes. Here, we describe the benefits of each method in an attempt to develop a more balanced view of how to utilize these model comparison techniques, and we outline the risks of focusing on a single method to make inferences about the overall utility of a model. Also, we make several suggestions about how applied research should evaluate candidate cognitive models, and we offer guidelines for future research aimed at identifying "good" models for decomposing and explaining participants' performance. | - |
dc.language | 영어 | - |
dc.publisher | American Psychological Association Inc. | - |
dc.title | To simulate or not? Comment on steingroever, Wetzels, and Wagenmakers (2014) | - |
dc.type | Article | - |
dc.identifier.doi | 10.1037/dec0000016 | - |
dc.citation.journaltitle | Decision | - |
dc.identifier.scopusid | 2-s2.0-85032867421 | - |
dc.citation.endpage | 191 | - |
dc.citation.number | 3 | - |
dc.citation.startpage | 184 | - |
dc.citation.volume | 1 | - |
dc.description.isOpenAccess | N | - |
dc.contributor.affiliatedAuthor | Ahn, Woo-Young | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.subject.keywordAuthor | Experience-based decision-making | - |
dc.subject.keywordAuthor | Iowa gambling task | - |
dc.subject.keywordAuthor | Mathematical modeling | - |
dc.subject.keywordAuthor | Reinforcement learning | - |
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