Using the ACT-R architecture to specify 39 quantitative process models of decision making

Détails

ID Serval
serval:BIB_EB01B9937AE6
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Titre
Using the ACT-R architecture to specify 39 quantitative process models of decision making
Périodique
Judgment and Decision Making
Auteur⸱e⸱s
Marewski J. N., Mehlhorn K.
ISSN
1930-2975
Statut éditorial
Publié
Date de publication
08/2011
Peer-reviewed
Oui
Volume
6
Numéro
6
Pages
439-519
Langue
anglais
Résumé
Hypotheses about decision processes are often formulated qualitatively and remain silent about the interplay of decision, memorial, and other cognitive processes. At the same time, existing decision models are specified at varying levels of detail, making it difficult to compare them. We provide a methodological primer on how detailed cognitive architectures such as ACT-R allow remedying these problems. To make our point, we address a controversy, namely, whether noncompensatory or compensatory processes better describe how people make decisions from the accessibility of memories. We specify 39 models of accessibility-based decision processes in ACT-R, including the noncompensatory recognition heuristic and various other popular noncompensatory and compensatory decision models. Additionally, to illustrate how such models can be tested, we conduct a model comparison, fitting the models to one experiment and letting them generalize to another. Behavioral data are best accounted for by race models. These race models embody the noncompensatory recognition heuristic and compensatory models as a race between competing processes, dissolving the dichotomy between existing decision models.
Mots-clé
ACT-R, Noncompensatory and compensatory models, Recognition heuristic, Race models, Cognitive architectures
Web of science
Création de la notice
14/10/2011 12:20
Dernière modification de la notice
20/08/2019 17:13
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