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A linear threshold model for optimal stopping behavior
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Baumann, Christiane, Singmann, Henrik, Gershman, Samuel J. and von Helversend, Bettina (2020) A linear threshold model for optimal stopping behavior. Proceedings of the National Academy of Sciences of the United States of America, 117 (23). pp. 12750-12755. doi:10.1073/pnas.2002312117
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WRAP-linear-threshold-model-optimal-stopping-behavior-Singmann-2020.pdf - Accepted Version - Requires a PDF viewer. Download (1170Kb) | Preview |
Official URL: https://doi.org/10.1073/pnas.2002312117
Abstract
In many real-life decisions, options are distributed in space and time, making it necessary to search sequentially through them, often without a chance to return to a rejected option. The optimal strategy in these tasks is to choose the first option that is above a threshold that depends on the current position in the sequence. The implicit decision-making strategies by humans vary but largely diverge from this optimal strategy. The reasons for this divergence remain unknown. We present a model of human stopping decisions in sequential decision-making tasks based on a linear threshold heuristic. The first two studies demonstrate that the linear threshold model accounts better for sequential decision making than existing models. Moreover, we show that the model accurately predicts participants’ search behavior in different environments. In the third study, we confirm that the model generalizes to a real-world problem, thus providing an important step toward understanding human sequential decision making.
| Item Type: | Journal Article | |||||||||||||||
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| Subjects: | B Philosophy. Psychology. Religion > BF Psychology H Social Sciences > HD Industries. Land use. Labor |
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| Divisions: | Faculty of Science > Psychology | |||||||||||||||
| Library of Congress Subject Headings (LCSH): | Decision making, Optimal stopping (Mathematical statistics), Adaptability (psychology), Cognition | |||||||||||||||
| Journal or Publication Title: | Proceedings of the National Academy of Sciences of the United States of America | |||||||||||||||
| Publisher: | National Academy of Sciences | |||||||||||||||
| ISSN: | 0027-8424 | |||||||||||||||
| Official Date: | 9 June 2020 | |||||||||||||||
| Dates: |
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| Volume: | 117 | |||||||||||||||
| Number: | 23 | |||||||||||||||
| Page Range: | pp. 12750-12755 | |||||||||||||||
| DOI: | 10.1073/pnas.2002312117 | |||||||||||||||
| Status: | Peer Reviewed | |||||||||||||||
| Publication Status: | Published | |||||||||||||||
| Access rights to Published version: | Restricted or Subscription Access | |||||||||||||||
| RIOXX Funder/Project Grant: |
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