The evolution of cooperation in spatial public goods game with conditional peer exclusion
Abstract
Social exclusion can prevent free riders from participating in social activities and deprive them of sharing cooperative benefits, which is an effective mechanism for the evolution of cooperation. However, traditional peer-exclusion strategies are unconditional, and as long as there are defectors in the group, they will pay a cost to exclude the defectors. In reality, one of the reasons for the complexity of these strategies is that individuals may react differently depending on the environment in which they are located. Based on this consideration, we introduce a kind of conditional peer-exclusion strategy in the spatial public goods game model. Specifically, the behavior of conditional exclusion depends on the number of defectors in the group and can be adjusted by a tolerance parameter. Only if the number of defectors in the group exceeds the tolerance threshold, conditional exclusion can be triggered to exclude defectors. We explore the effects of parameters such as tolerance, exclusion cost, and probability of exclusion success on the evolution of cooperation. Simulation results confirmed that conditional exclusion can greatly reduce the threshold values of the synergy factor above which cooperation can emerge. Especially, when the tolerance is low, very small synergy factors can promote the population to achieve a high level of cooperation. Moreover, even if the probability of exclusion success is low, or the unit exclusion cost is relatively high, conditional exclusion is effective in promoting cooperation. These results allow us to better understand the role of exclusion strategies in the emergence of cooperation.
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Self-citationEvolutionary dynamics in public goods games with general frequency-dependent returns
Wang, Q., Liu, Y., Chen, X., & Szolnoki, A. (2026) · Physica D Nonlinear Phenomena · doi:10.1016/j.physd.2026.135303 · Cited by 1 · see citing works
Aspiration-Based Learning in k-Hop Best-Shot Binary Networked Public Goods Games
Chen, Z., Dai, K., Jin, X., Hu, L., & Wang, Y. (2023) · Mathematics · doi:10.3390/math11143037 · Cited by 1 · see citing works
Sun, X., Huang, Z., Kang, H., Li, Z., Shen, Y., & Chen, Q. (2024) · Physics Letters A · doi:10.1016/j.physleta.2024.129759
Evolution of Cooperation in Structured Populations through Pool Exclusion Strategy
Hua, S., Xu, M., & Liu, L. (2024) · Chinese Control Conference (CCC) · doi:10.23919/ccc63176.2024.10662117
LIU, Y., Ma, J., XU, X., & LI, Y. (2024) · Advances in Complex Systems · doi:10.1142/s0219525924500085
Wang, Q., & Chen, X. (2026) · Applied Mathematics and Computation · doi:10.1016/j.amc.2026.130239
- Authors
- Quan, J., Li, X., & Wang, X.
- Affiliations
- Wuhan University of Technology (CN)
- Wuhan University (CN)
- Corresponding author
- Quan, Ji
- Wang, Xianjia
- Venue
- Chaos An Interdisciplinary Journal of Nonlinear Science
- Publisher
- AIP Publishing
- Published
- 2019-10-01
- Volume
- 29
- Issue
- 10
- Pages
- 103137-103137
- ISSN
- 1054-1500 (ISSN-L)
- 1089-7682
- OpenAlex
- W2981542964
- Cited by
- 53
- References
- 75
- Citations by year
- 2026: 3 · 2025: 4 · 2024: 10 · 2023: 10 · 2022: 9 · 2021: 8 · 2020: 8 · 2019: 1
- FWCI
- 13.06
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Chaos An Interdisciplinary Journal of Nonlinear Science (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Natural Science Foundation of China (71501149, 71871171, 71871173)
- Fundamental Research Funds for the Central Universities (WUT:2019VI029)
- 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, spatial public goods game, social exclusion, free-riding, tolerance threshold, synergy factor, defectors
- MeSH terms
- Cooperative Behavior, Game Theory, Humans, Models, Theoretical
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