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Cited by 165

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

Does strong heterogeneity promote cooperation by group interactions?

Open access
Perc, Matjaž·2011·New Journal of Physics

Abstract

Previous research has highlighted the importance of strong heterogeneity for the successful evolution of cooperation in games governed by pairwise interactions. Here we determine to what extent this is true for games governed by group interactions. We therefore study the evolution of cooperation in the public goods game on the square lattice, the triangular lattice, and the random regular graph, whereby the payoffs are distributed either uniformly or exponentially amongst the players by assigning to them individual scaling factors that determine the share of the public good they will receive. We find that uniformly distributed public goods are more successful in maintaining high levels of cooperation than exponentially distributed public goods. This is not in agreement with previous results on games governed by pairwise interactions, indicating that group interactions may be less susceptible to the promotion of cooperation by means of strong heterogeneity than originally assumed, and that the role of strongly heterogeneous states should be reexamined for other types of games.

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Crossref · 10.1088/1367-2630/13/12/123027

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Metadata

Authors
Perc, M.
Venue
New Journal of Physics
Published
2011-12-21
Volume
13
Issue
12
Pages
123027
ISSN
1367-2630 (ISSN-L)
OpenAlex
W2045134910
Cited by
165
References
7
FWCI
45.01
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Does strong heterogeneity promote cooperation by group interactions? https://app.cochat.ai/papers/10.1088/1367-2630/13/12/123027
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Perc, M. (2011). Does strong heterogeneity promote cooperation by group interactions? New Journal of Physics. https://doi.org/10.1088/1367-2630/13/12/123027

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.