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Payoff-based learning best explains the rate of decline in cooperation across 237 public-goods games

Abstract

What motivates human behaviour in social dilemmas? The results of public goods games are commonly interpreted as showing that humans are altruistically motivated to benefit others. However, there is a competing ‘confused learners’ hypothesis: that individuals start the game either uncertain or mistaken (confused) and then learn from experience how to improve their payoff (payoff-based learning). Here we (1) show that these competing hypotheses can be differentiated by how they predict contributions should decline over time; and (2) use metadata from 237 published public goods games to test between these competing hypotheses. We found, as predicted by the confused learners hypothesis, that contributions declined faster when individuals had more influence over their own payoffs. This predicted relationship arises because more influence leads to a greater correlation between contributions and payoffs, facilitating learning. Our results suggest that humans, in general, are not altruistically motivated to benefit others but instead learn to help themselves.

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Fig. 1: The confused learners hypothesis.
Fig. 2: Payoff-based learning in a black box public goods game.
Fig. 3: Influence explains variation in the rate at which contributions change.
Fig. 4: Competing hypotheses.

Data availability

Figures 2 and 3 and Supplementary Figs. 35 have associated raw data available from the Dryad Digital Repository (https://doi.org/10.5061/dryad.fn2z34tsv). There are no restrictions on data availability.

Code availability

The R code for the simulation study is included in the Dryad Digital Repository (https://doi.org/10.5061/dryad.fn2z34tsv).

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Acknowledgements

Funding provided by Calleva Research Centre for Evolution and Human Sciences, Magdalen College, Oxford (M.N.B.-C. and S.A.W.), ERC advanced grant 834164 (S.A.W.) and the University of Lausanne, Switzerland (M.N.B.-C.). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. Thanks to Z. Griffiths for help with data collection, L. Lehmann for discussions and P. Barclay for reviewing the manuscript.

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M.N.B.-C. and S.A.W. conceived and designed the research. M.N.B.-C. collected the data and performed the analyses. M.N.B.-C. and S.A.W. wrote the article.

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Correspondence to Maxwell N. Burton-Chellew.

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Burton-Chellew, M.N., West, S.A. Payoff-based learning best explains the rate of decline in cooperation across 237 public-goods games. Nat Hum Behav 5, 1330–1338 (2021). https://doi.org/10.1038/s41562-021-01107-7

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