Racing for the city: The recognition heuristic and compensatory alternatives

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Serval ID
serval:BIB_87428DDC6E92
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Title
Racing for the city: The recognition heuristic and compensatory alternatives
Title of the conference
Proceedings of the 33rd Annual Conference of the Cognitive Science Society
Author(s)
Mehlhorn K., Marewski J. N.
Publisher
Austin, TX: Cognitive Science Society
ISBN
978-0-9768318-7-7
Publication state
Published
Issued date
2011
Peer-reviewed
Oui
Editor
Carlson L., Hölscher C., Shipley T.
Pages
360-365
Language
english
Abstract
In the last decade a debate in the decision making literature has centered on the question whether decisions can be better described by simple non-compensatory heuristics or by more complex compensatory strategies. We argue that this debate should be led at a higher level of precision Theories about decision strategies are implemented at different levels of description and they often only make verbal, qualitative predictions. This makes it difficult to compare between them and to test them against quantitative process data. A way to make theories comparable and improve the precision of their predictions is to model them within one computational framework. Using the example of the recognition heuristic, we show how simplifying dichotomies such as the one between non-compensatory and compensatory decision strategies can dissolve when using detailed quantitative models.
Keywords
Recognition heuristic, Compensatory strategies, Cognitive model, ACT-R
Create date
14/10/2011 11:58
Last modification date
20/08/2019 14:46
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