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Why Copy Others? Insights from the Social Learning Strategies Tournament
Open accessAbstract
It Pays to Be a Copy Cat: Does it pay to copy what others do? Rendell et al. (p. 208 ) elected to copy Robert Axelrod's 1979 tournament in which strategies for playing the iterated prisoner's dilemma game were pitted against each other until an overall winner emerged—the tit-for-tat strategy. In the 2008 tournament, 100 social learning strategies designed to cope with a changing environment competed against each other; the winning strategy involved sampling the behaviors of other players periodically, rather than exploring the environment alone.
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“Its effectiveness can be attributed to the flexibility with which participants engage in these two mechanisms [Enquist et al., 2008, Rendell et al., 2010, Mesoudi and Thornton, 2018].”
From Artificial Generational Intelligence: Cultural Accumulation in Reinforcement Learning (2024) · cites this paper as Rendell et al., 2010
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Citations
Cites
Model selection and multimodel inference: a practical information-theoretic approach.
Guthery, F. S., Burnham, K. P., & Anderson, D. R. (2003) · The Journal of Wildlife Management · doi:10.2307/3802723 · Cited by 41,495
Axelrod, R., & Hamilton, W. D. (1981) · Science · doi:10.1126/science.7466396 · Cited by 20,065
Culture and the Evolutionary Process
Griesemer, J. R., Boyd, R. T., & Richerson, P. J. (1986) · Ornithological Applications · doi:10.2307/1367778 · Cited by 7,133
Self-citationFinite-time Analysis of the Multiarmed Bandit Problem
Auer, P., Cesa-Bianchi, N., & Fischer, P. (2002) · Machine Learning · doi:10.1023/a:1013689704352 · Cited by 6,033
Resource Competition and Community Structure
Hassell, M. P., & Tilman, D. G. (1984) · Journal of Animal Ecology · doi:10.2307/4549 · Cited by 4,238
Not By Genes Alone: How Culture Transformed Human Evolution
Richerson, P. J., & Boyd, R. (2004) · doi:10.7208/chicago/9780226712130.001.0001 · Cited by 2,793
Self-citationHenrich, J., & Gil-White, F. J. (2001) · Evolution and Human Behavior · doi:10.1016/s1090-5138(00)00071-4 · Cited by 2,500
Evolutionary Dynamics: Exploring the Equations of Life
NOWAK, M. A. (2006) · doi:10.2307/j.ctvjghw98 · Cited by 2,438
Experimental Study of Inequality and Unpredictability in an Artificial Cultural Market
Salganik, M. J., Dodds, P. S., & Watts, D. J. (2006) · Science · doi:10.1126/science.1121066 · Cited by 2,231
The evolution of foresight: What is mental time travel, and is it unique to humans?
Suddendorf, T., & Corballis, M. C. (2007) · Behavioral and Brain Sciences · doi:10.1017/s0140525x07001975 · Cited by 2,031
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Miu, E., Rendell, L. E., Bowles, S., Boyd, R., Cownden, D., Enquist, M., Eriksson, K., Feldman, M. W., Lillicrap, T., McElreath, R. L., et al. (2024) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2024.03.22.586239 · Cited by 1
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Carr, J. R. (2013) · University Libraries (University of Maryland)
Climate Change Governance, Cooperation and Self-organization
Santos, F. C. (2016) · Conference on Artificial Life (ALIFE) · doi:10.7551/978-0-262-33936-0-ch008
Ormerod, P. (2012) · Security Informatics · doi:10.1186/2190-8532-1-16
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Efferson, C. M. (2012) · The Economic Journal · doi:10.1111/j.1468-0297.2012.02538.x
Evolution and Learning in Heterogeneous Environments
Jones, D. (2015) · Goldsmiths (University of London) · doi:10.25602/gold.00015078
How cultural transmission facilitates a long juvenile learning periodPreprint
Baldini, R. (2014) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/007930
Stable Learning and Foraging Strategies
Cownden, D. (2012)
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Agliari, E., Adriano Barra, A., Galluzzi, A., Requena-Silvente, F., & Tantari, D. (2015) · RePEc: Research Papers in Economics · doi:10.48550/arxiv.1503.06020
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Gao, S. (2014) · Libraries and Cultural Resources (University of Calgary) · doi:10.11575/prism/25365
de, M. M., & Rossi, L. F. (2014) · Conference on Artificial Life (ALIFE) · doi:10.1162/978-0-262-32621-6-ch152
Synergy between intention recognition and commitments in cooperation
Han, T. A., Santos, F. C., & Lenaerts, T. (2015)
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Kulke, E. (2015)
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Mitterbacher, K. (2009) · Routledge eBooks · doi:10.4324/9780203884799.ch4
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Molleman, L. (2014) · University of Groningen research database (University of Groningen / Centre for Information Technology)
Kupán, K. (2014) · Eötvös Loránd Tudományegyetem · doi:10.15476/elte.2013.001
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Newman, M. C. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-809642-0.00002-9
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Takeda, K., Hisakado, M., & Mori, S. (2020) · Springer proceedings in complexity · doi:10.1007/978-3-030-38965-9_14
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Metadata
- Authors
- Rendell, L., Boyd, R., Cownden, D., Enquist, M., Eriksson, K., Feldman, M. W., Fogarty, L., Ghirlanda, S., Lillicrap, T., & Laland, K. N.
- Affiliations
- University of St Andrews (GB)
- University of California, Los Angeles (US)
- Queen's University (CA)
- Stockholm University (SE)
- Stanford University (US)
- Corresponding author
- Rendell, L.
- Laland, K. N.
- ORCID
- Venue
- Science
- Published
- 2010-04-09
- Volume
- 328
- Issue
- 5975
- Pages
- 208-213
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC2989663
- OpenAlex
- W2038900621
- Cited by
- 811
- References
- 45
- Citations by year
- 2026: 26 · 2025: 41 · 2024: 70 · 2023: 41 · 2022: 49 · 2021: 55 · 2020: 45 · 2019: 55 · 2018: 48 · 2017: 40 · 2016: 54 · 2015: 62 · 2014: 51 · 2013: 48 · 2012: 67
- FWCI
- 1771.34
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- OSF Preprints (OSF Preprints) (submittedVersion)
- Funders
- National Institute of General Medical Sciences (R01GM028016)
- Topics
- Social Sciences › Cultural Studies › Language and cultural evolution
- Social Sciences › Sociology and Political Science › Evolutionary Game Theory and Cooperation
- Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
- Keywords
- social learning, copying behavior, trial-and-error learning, information filtering, adaptive behavior, learning strategies, evolutionary game theory
- MeSH terms
- Cooperative Behavior, Cultural Evolution, Games, Experimental, Humans, Imitative Behavior, Learning, Problem Solving, Social Behavior, Software, Linear Models, Observation
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