Conditions under which faithful cultural transmission through teaching promotes cumulative cultural evolution.


Journal

Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288

Informations de publication

Date de publication:
28 Nov 2023
Historique:
received: 22 03 2023
accepted: 08 11 2023
medline: 30 11 2023
pubmed: 29 11 2023
entrez: 28 11 2023
Statut: epublish

Résumé

It has been argued that teaching promotes the accurate transmission of cultural traits and eventually leads to cumulative cultural evolution (CCE). However, previous studies have questioned this argument. In this study, we modified the action sequences model into a network exploring model with reinforcement learning to examine the conditions under which teaching promotes CCE. Our model incorporates a time trade-off between innovation and teaching. Simulations revealed that the positive influence of teaching on CCE depends on task difficulty. When the task was too difficult and advanced, such that it could not be accomplished through individual learning within a limited time, spending more time on teaching-even at the expense of time for innovation-contributed to CCE. On the contrary, the easier the task, the more time was spent on innovation than on teaching, which contributed to the improvement of performance. These findings suggest that teaching becomes more valuable as cultures become more complex. Therefore, humanity must have co-evolved a complex cumulative culture and teaching that supports cultural fidelity.

Identifiants

pubmed: 38017047
doi: 10.1038/s41598-023-47018-7
pii: 10.1038/s41598-023-47018-7
pmc: PMC10684533
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

20986

Subventions

Organisme : Japan Society for the Promotion of Science
ID : 20J20818
Organisme : Japan Society for the Promotion of Science
ID : 16H06324

Informations de copyright

© 2023. The Author(s).

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Auteurs

Seiya Nakata (S)

Graduate School of Humanities and Human Sciences, Hokkaido University, Sapporo, Japan.
Japan Society for the Promotion of Science, Tokyo, Japan.

Masanori Takezawa (M)

Center for Experimental Research in Social Sciences, Hokkaido University, Sapporo, Japan. m.takezawa@let.hokudai.ac.jp.
Center for Human Nature, Artificial Intelligence and Neuroscience, Hokkaido University, Sapporo, Japan. m.takezawa@let.hokudai.ac.jp.
Faculty of Humanities and Human Sciences, Hokkaido University, N10W7, Kita-ku, Sapporo, Hokkaido, 060-0810, Japan. m.takezawa@let.hokudai.ac.jp.

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Classifications MeSH