Signalling boosts the evolution of cooperation in repeated group interactions
Open accessAbstract
Many biological and social systems show significant levels of collective action. Several cooperation mechanisms have been proposed, yet they have been mostly studied independently. Among these, direct reciprocity supports cooperation on the basis of repeated interactions among individuals. Signals and quorum dynamics may also drive cooperation. Here, we resort to an evolutionary game-theoretical model to jointly analyse these two mechanisms and study the conditions in which evolution selects for direct reciprocity, signalling, or their combination. We show that signalling alone leads to higher levels of cooperation than when combined with reciprocity, while offering additional robustness against errors. Specifically, successful strategies in the realm of direct reciprocity are often not selected in the presence of signalling, and memory of past interactions is only exploited opportunistically in the case of earlier coordination failure. Differently, signalling always evolves, even when costly. In the light of these results, it may be easier to understand why direct reciprocity has been observed only in a limited number of cases among non-humans, whereas signalling is widespread at all levels of complexity.
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Real interactions are repeated rather than one-shot.
“Indeed, real interactions are repeated rather than the one-shot interaction assumed above [11, 10, 30, 33, 28].”
From Conditional investment strategy in evolutionary trust games with repeated group interactions (2022) · cites this paper as [30]
In repeated interactions, investors have the opportunity to adjust their actions according to the investment environment they encountered.
“Furthermore, in repeated interactions, investors have the opportunity to adjust their actions according to the investment environment they encountered [30, 34, 28].”
From Conditional investment strategy in evolutionary trust games with repeated group interactions (2022) · cites this paper as [30]
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Cited by
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Conditional investment strategy in evolutionary trust games with repeated group interactions
Liu, L., & Chen, X. (2022) · Information Sciences · doi:10.1016/j.ins.2022.07.073 · Cited by 45 · see citing works
- Authors
- Martinez-Vaquero, L. A., Santos, F. C., & Trianni, V.
- Affiliations
- National Research Council (IT)
- Instituto de Engenharia de Sistemas e Computadores Investigação e Desenvolvimento (PT)
- Venue
- Journal of The Royal Society Interface
- Publisher
- The Royal Society
- Published
- 2020-11
- Volume
- 17
- Issue
- 172
- Pages
- 20200635
- ISSN
- 1742-5662 (ISSN-L)
- 1742-5689
- PMC
- PMC7729056
- OpenAlex
- W3095652294
- Cited by
- 11
- References
- 60
- Citations by year
- 2025: 3 · 2024: 2 · 2023: 3 · 2022: 3
- FWCI
- 2.01
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- Locations
- Journal of The Royal Society Interface (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- European Research Consortium for Informatics and Mathematics (Alain Bensoussan Fellowship)
- Fundação para a Ciência e a Tecnologia (PTDC/EEI-SII/5081/2014, PTDC/MAT/STA/3358/2014, UIDB/50021/2020)
- H2020 LEIT Information and Communication Technologies (952215)
- FP7 People: Marie-Curie Actions (631297)
- 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, direct reciprocity, signaling, costly signaling, error resilience, collective action, evolutionary game theory
- MeSH terms
- Cooperative Behavior, Biological Evolution, Game Theory, Memory, Models, Theoretical
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