Evolutionary Dynamics of Group Cooperation on Heterogeneous Higher-Order Networks

Group cooperation is vital for the prosperity and development of human societies. Previous studies have demonstrated that network structures and their structural heterogeneities significantly affect the evolution of cooperation. Most of these studies focus on traditional networks, where edges represent pairwise interactions. However, interactions frequently go beyond pairwise connections, occurring within groups of varying sizes and exhibiting nonlinear effects. Higher-order networks capture such characteristics by allowing general group interactions among more than two individuals with hyperedges. Here, we explore the effect of degree heterogeneity and order (i.e., group size) heterogeneity on the evolution of cooperation under both linear public goods games (PGGs) and nonlinear multiplayer snowdrift games (MSGs). We find that compared with degree homogeneity, strong degree heterogeneity may inhibit the evolution of cooperation in public goods games whereas in multiplayer snowdrift games, it can instead confer additional benefits for cooperation. Moreover, our results show that order heterogeneity reduces the threshold for the evolution of cooperation in multiplayer snowdrift games while having an almost negligible impact on cooperation in public goods games. Through extensive simulations, we reveal that such differences result from the distinct payoff structures of these two games. Our work thus highlights that how structural heterogeneities of higher-order networks affect the evolution of cooperation depends on the specific games employed, and it is necessary to consider both linear and nonlinear games to uncover the intricate and unique effect of higher-order interactions on evolutionary outcomes.

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Publication Details

Journal
IEEE Transactions on Network Science and Engineering
Published
2025-06-09
DOI
https://doi.org/10.1109/tnse.2025.3577657
Citations
1
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
1.32
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article

Evolutionary Dynamics of Group Cooperation on Heterogeneous Higher-Order Networks

Zhixin Gao, Bingxin Lin, Lei Zhou
1 citations
IEEE Transactions on Network Science and Engineering
Opinion Dynamics and Social Influence
1.32
article

Evolutionary Dynamics of Group Cooperation on Heterogeneous Higher-Order Networks

Zhixin Gao, Bingxin Lin, Lei Zhou
article en
1 citations

Abstract

Group cooperation is vital for the prosperity and development of human societies. Previous studies have demonstrated that network structures and their structural heterogeneities significantly affect the evolution of cooperation. Most of these studies focus on traditional networks, where edges represent pairwise interactions. However, interactions frequently go beyond pairwise connections, occurring within groups of varying sizes and exhibiting nonlinear effects. Higher-order networks capture such characteristics by allowing general group interactions among more than two individuals with hyperedges. Here, we explore the effect of degree heterogeneity and order (i.e., group size) heterogeneity on the evolution of cooperation under both linear public goods games (PGGs) and nonlinear multiplayer snowdrift games (MSGs). We find that compared with degree homogeneity, strong degree heterogeneity may inhibit the evolution of cooperation in public goods games whereas in multiplayer snowdrift games, it can instead confer additional benefits for cooperation. Moreover, our results show that order heterogeneity reduces the threshold for the evolution of cooperation in multiplayer snowdrift games while having an almost negligible impact on cooperation in public goods games. Through extensive simulations, we reveal that such differences result from the distinct payoff structures of these two games. Our work thus highlights that how structural heterogeneities of higher-order networks affect the evolution of cooperation depends on the specific games employed, and it is necessary to consider both linear and nonlinear games to uncover the intricate and unique effect of higher-order interactions on evolutionary outcomes.

IEEE Transactions on Network Science and EngineeringVol. 12(6)
Beijing Institute of Technology (CN), Wuhan University (CN)
Partnerships for the goals
Openalex Percentile: Top 19%
Opinion Dynamics and Social Influence
1.32
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Evolutionary Dynamics of Group Cooperation on Heterogeneous Higher-Order Networks — Zhixin Gao, Bingxin Lin, et al. · IEEE Transactions on Network Science and Engineering (2025) | TGRS Research Map | TGRS