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Local sampling with momentum accounts for human random sequence generation

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Castillo, Lucas, Leon-Villagra, Pablo, Chater, Nick and Sanborn, Adam N. (2021) Local sampling with momentum accounts for human random sequence generation. Proceedings of the Annual Meeting of the Cognitive Science Society, 43 . ISSN 1069-7977.

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Official URL: https://escholarship.org/uc/item/3gz154kg

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Abstract

Many models of cognition assume that people can generate independent samples, yet people fail to do so in random generation tasks. One prominent explanation for this behavior is that people use learned schemas. Instead, we propose that deviations from randomness arise from people sampling locally rather than independently. To test these explanations, we teach people one- and two-dimensional arrangements of syllables and ask them to generate random sequences from them. Although our results reproduce characteristic features of human random generation, such as a preference for adjacent items and an avoidance of repetitions, we also find an effect of dimensionality on the patterns people produce. Furthermore, model comparisons revealed that local sampling accounted better for participants' sequences than a schema account. Finally, evaluating the importance of each models' constituents, we show that the local sampling model proposed new states based on its current trajectory, rather than an inhibition-of-return-like principle.

Item Type: Journal Article
Subjects: B Philosophy. Psychology. Religion > BC Logic
B Philosophy. Psychology. Religion > BF Psychology
H Social Sciences > HA Statistics
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
Library of Congress Subject Headings (LCSH): Inference, Cognition , Random data (Statistics) , Sampling (Statistics), Probabilities
Journal or Publication Title: Proceedings of the Annual Meeting of the Cognitive Science Society
Publisher: The Cognitive Science Society
ISSN: 1069-7977
Official Date: 2021
Dates:
DateEvent
2021Published
13 April 2021Accepted
Volume: 43
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 1 October 2021
Date of first compliant Open Access: 4 October 2021
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
817492- SAMPLINGEuropean Research Councilhttp://dx.doi.org/10.13039/501100000781
Is Part Of: 1
Open Access Version:
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