Cited by 277Evolutionary Game Theory and CooperationExperimental Behavioral Economics StudiesGame Theory and Applications

Evolution of cooperation in stochastic games

Hilbe, Christian, Šimsa, Štěpán, Chatterjee, Krishnendu, Nowak, Martin A.·2018·Nature

Abstract

Social dilemmas occur when incentives for individuals are misaligned with group interests 1-7. According to the 'tragedy of the commons', these misalignments can lead to overexploitation and collapse of public resources. The resulting behaviours can be analysed with the tools of game theory 8. The theory of direct reciprocity 9-15 suggests that repeated interactions can alleviate such dilemmas, but previous work has assumed that the public resource remains constant over time. Here we introduce the idea that the public resource is instead changeable and depends on the strategic choices of individuals. An intuitive scenario is that cooperation increases the public resource, whereas defection decreases it. Thus, cooperation allows the possibility of playing a more valuable game with higher payoffs, whereas defection leads to a less valuable game. We analyse this idea using the theory of stochastic games 16-19 and evolutionary game theory. We find that the dependence of the public resource on previous interactions can greatly enhance the propensity for cooperation. For these results, the interaction between reciprocity and payoff feedback is crucial: neither repeated interactions in a constant environment nor single interactions in a changing environment yield similar cooperation rates. Our framework shows which feedbacks between exploitation and environment-either naturally occurring or designed-help to overcome social dilemmas.

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Crossref · 10.1038/s41586-018-0277-x

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  • Techniques from game theory can be valuable in modeling behavior, e.g., to explore cooperation in the face of a depleting resource.

    “In addition to ABMs, techniques from game theory can be valuable in modeling behavior, e.g., to explore cooperation in the face of a depleting resource [344].”

    From Tackling climate change with machine learning (2023) · cites this paper as [344]

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Authors
Hilbe, C., Šimsa, Š., Chatterjee, K., & Nowak, M. A.
Affiliations
  • Harvard University (US)
  • Charles University (CZ)
  • Institute of Science and Technology Austria (AT)
Corresponding author
  • Hilbe, Christian
  • Chatterjee, Krishnendu
  • Nowak, Martin A.
Venue
Nature
Published
2018-07
Volume
559
Issue
7713
Pages
246-249
ISSN
  • 0028-0836 (ISSN-L)
  • 1476-4687
OpenAlex
W2811498230
Cited by
277
References
85
Citations by year
2026: 34 · 2025: 40 · 2024: 42 · 2023: 38 · 2022: 38 · 2021: 31 · 2020: 29 · 2019: 21 · 2018: 4
FWCI
48.26
Type
journal article
Language
en
Open access
closed
Locations
  • Nature (publishedVersion)
  • PubMed (publishedVersion)
  • RePEc: Research Papers in Economics (submittedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Evolutionary Game Theory and Cooperation
  • Social Sciences › Safety Research › Experimental Behavioral Economics Studies
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Game Theory and Applications
Keywords
evolution of cooperation, stochastic games, social dilemmas, public goods, direct reciprocity, repeated interaction, tragedy of the commons, environmental change
MeSH terms
Cooperative Behavior, Decision Making, Biological Evolution, Game Theory, Group Processes, Probability, Stochastic Processes, Feedback, Psychological

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