Complex cognitive algorithms preserved by selective social learning in experimental populations.

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Title: Complex cognitive algorithms preserved by selective social learning in experimental populations.
Authors: Thompson, B., Opheusden, B., Sumers, T., Griffiths, T. L.
Source: Science (pre-March 2025). 4/1/2022, Vol. 376 Issue 6588, p95-98. 4p. 4 Diagrams.
Subjects: Social learning, Social evolution, Cognitive ability, Algorithms, Decision making
Abstract: Many human abilities rely on cognitive algorithms discovered by previous generations. Cultural accumulation of innovative algorithms is hard to explain because complex concepts are difficult to pass on. We found that selective social learning preserved rare discoveries of exceptional algorithms in a large experimental simulation of cultural evolution. Participants (N = 3450) faced a difficult sequential decision problem (sorting an unknown sequence of numbers) and transmitted solutions across 12 generations in 20 populations. Several known sorting algorithms were discovered. Complex algorithms persisted when participants could choose who to learn from but frequently became extinct in populations lacking this selection process, converging on highly transmissible lower-performance algorithms. These results provide experimental evidence for hypothesized links between sociality and cognitive function in humans. [ABSTRACT FROM AUTHOR]
Copyright of Science (pre-March 2025) is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Complex cognitive algorithms preserved by selective social learning in experimental populations.
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  Data: <searchLink fieldCode="AR" term="%22Thompson%2C+B%2E%22">Thompson, B.</searchLink><br /><searchLink fieldCode="AR" term="%22Opheusden%2C+B%2E%22">Opheusden, B.</searchLink><br /><searchLink fieldCode="AR" term="%22Sumers%2C+T%2E%22">Sumers, T.</searchLink><br /><searchLink fieldCode="AR" term="%22Griffiths%2C+T%2E+L%2E%22">Griffiths, T. L.</searchLink>
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  Data: <searchLink fieldCode="JN" term="%22Science+%28pre-March+2025%29%22">Science (pre-March 2025)</searchLink>. 4/1/2022, Vol. 376 Issue 6588, p95-98. 4p. 4 Diagrams.
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  Data: <searchLink fieldCode="DE" term="%22Social+learning%22">Social learning</searchLink><br /><searchLink fieldCode="DE" term="%22Social+evolution%22">Social evolution</searchLink><br /><searchLink fieldCode="DE" term="%22Cognitive+ability%22">Cognitive ability</searchLink><br /><searchLink fieldCode="DE" term="%22Algorithms%22">Algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+making%22">Decision making</searchLink>
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  Label: Abstract
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  Data: Many human abilities rely on cognitive algorithms discovered by previous generations. Cultural accumulation of innovative algorithms is hard to explain because complex concepts are difficult to pass on. We found that selective social learning preserved rare discoveries of exceptional algorithms in a large experimental simulation of cultural evolution. Participants (N = 3450) faced a difficult sequential decision problem (sorting an unknown sequence of numbers) and transmitted solutions across 12 generations in 20 populations. Several known sorting algorithms were discovered. Complex algorithms persisted when participants could choose who to learn from but frequently became extinct in populations lacking this selection process, converging on highly transmissible lower-performance algorithms. These results provide experimental evidence for hypothesized links between sociality and cognitive function in humans. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Science (pre-March 2025) is the property of American Association for the Advancement of Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1126/science.abn0915
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        Text: English
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      – SubjectFull: Social learning
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      – SubjectFull: Social evolution
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      – SubjectFull: Cognitive ability
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      – SubjectFull: Algorithms
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      – SubjectFull: Decision making
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              Text: 4/1/2022
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              Y: 2022
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