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Explaining the flaws in human random generation as local sampling with momentum
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Castillo, Lucas, León-Villagrá, Pablo, Chater, Nick and Sanborn, Adam N. (2024) Explaining the flaws in human random generation as local sampling with momentum. PLOS Computational Biology, 20 (1). e1011739. doi:10.1371/journal.pcbi.1011739 ISSN 1553-7358.
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Official URL: https://doi.org/10.1371/journal.pcbi.1011739
Abstract
In many tasks, human behavior is far noisier than is optimal. Yet when asked to behave randomly, people are typically too predictable. We argue that these apparently contrasting observations have the same origin: the operation of a general-purpose local sampling algorithm for probabilistic inference. This account makes distinctive predictions regarding random sequence generation, not predicted by previous accounts—which suggests that randomness is produced by inhibition of habitual behavior, striving for unpredictability. We verify these predictions in two experiments: people show the same deviations from randomness when randomly generating from non-uniform or recently-learned distributions. In addition, our data show a novel signature behavior, that people’s sequences have too few changes of trajectory, which argues against the specific local sampling algorithms that have been proposed in past work with other tasks. Using computational modeling, we show that local sampling where direction is maintained across trials best explains our data, which suggests it may be used in other tasks too. While local sampling has previously explained why people are unpredictable in standard cognitive tasks, here it also explains why human random sequences are not unpredictable enough.
Item Type: | Journal Article | ||||||
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Subjects: | B Philosophy. Psychology. Religion > BF Psychology Q Science > Q Science (General) Q Science > QA Mathematics Q Science > QH Natural history |
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Divisions: | Faculty of Social Sciences > Warwick Business School > Behavioural Science Faculty of Science, Engineering and Medicine > Science > Psychology Faculty of Social Sciences > Warwick Business School |
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SWORD Depositor: | Library Publications Router | ||||||
Library of Congress Subject Headings (LCSH): | Psychology, Experimental , Cognition, Information theory, Cognitive psychology , Random walks (Mathematics), Computational biology | ||||||
Journal or Publication Title: | PLOS Computational Biology | ||||||
Publisher: | Public Library of Science | ||||||
ISSN: | 1553-7358 | ||||||
Official Date: | 5 January 2024 | ||||||
Dates: |
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Volume: | 20 | ||||||
Number: | 1 | ||||||
Article Number: | e1011739 | ||||||
DOI: | 10.1371/journal.pcbi.1011739 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Open Access (Creative Commons) | ||||||
Date of first compliant deposit: | 19 January 2024 | ||||||
Date of first compliant Open Access: | 26 January 2024 | ||||||
RIOXX Funder/Project Grant: |
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