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ERIC Number: EJ820984
Record Type: Journal
Publication Date: 2008-Dec
Pages: 27
Abstractor: As Provided
Reference Count: 40
ISSN: ISSN-0364-0213
Comparison of Decision Learning Models Using the Generalization Criterion Method
Ahn, Woo-Young; Busemeyer, Jerome R.; Wagenmakers, Eric-Jan; Stout, Julie C.
Cognitive Science, v32 n8 p1376-1402 Dec 2008
It is a hallmark of a good model to make accurate "a priori" predictions to new conditions (Busemeyer & Wang, 2000). This study compared 8 decision learning models with respect to their generalizability. Participants performed 2 tasks (the Iowa Gambling Task and the Soochow Gambling Task), and each model made a priori predictions by estimating the parameters for each participant from 1 task and using those same parameters to predict on the other task. Three methods were used to evaluate the models at the individual level of analysis. The first method used a post hoc fit criterion, the second method used a generalization criterion for short-term predictions, and the third method again used a generalization criterion for long-term predictions. The results suggest that the models with the prospect utility function can make generalizable predictions to new conditions, and different learning models are needed for making short-versus long-term predictions on simple gambling tasks. (Contains 6 figures, 6 tables and 5 notes.)
Psychology Press. Available from: Taylor & Francis, Ltd. 325 Chestnut Street Suite 800, Philadelphia, PA 19106. Tel: 800-354-1420; Fax: 215-625-2940; Web site:
Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A