EconPapers    
Economics at your fingertips  
 

Spatial public goods game on hypergraphs with particle swarm intelligence

Shun Gao, Liming Zhang, Qionglin Dai, Haihong Li, Claudio J. Tessone and Junzhong Yang

Chaos, Solitons & Fractals, 2025, vol. 201, issue P1

Abstract: Particle swarm optimization (PSO) has emerged as a powerful tool in evolutionary game theory, particularly for enhancing cooperation in spatial public goods games (PGGs). While existing research often focuses on one-on-one pairwise interactions, the role of PSO in fostering cooperation under many-body interactions on hypergraphs remains unexplored. Here, we extend spatial PGGs to uniform random hypergraphs (URHs) with tunable group sizes and integrate the PSO algorithm into evolutionary dynamics for agents to adapt their strategies. We consider two scenarios for the PSO, one in which cognitive component and social learning are interdependent, and the other where they are independent. We find that in the former case, PSO can promote cooperation over a larger parameter range compared to the Fermi strategy updating rule. Moreover, larger groups are more effective in promoting cooperation on URHs, enabling the population to reach a high level of cooperation. Notably, combining smaller self-cognitive adjustments with larger social influences can significantly enhance cooperation. Furthermore, in the independent case where the constraint between individual and social learning weights is relaxed, cooperation could be optimized with environment-dependent parameter settings. In particular, individual learning buffers cooperators in harsh environments, while social learning accelerates cooperation in favorable conditions. Our research underscores the effectiveness of PSO in addressing social dilemmas and advances the understanding of the interaction between individual learning and social learning in complex networked systems.

Keywords: Spatial public goods game; Particle swarm intelligence; Cooperation; Hypergraphs (search for similar items in EconPapers)
Date: 2025
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077925013177
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:201:y:2025:i:p1:s0960077925013177

DOI: 10.1016/j.chaos.2025.117304

Access Statistics for this article

Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros

More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().

 
Page updated 2026-03-28
Handle: RePEc:eee:chsofr:v:201:y:2025:i:p1:s0960077925013177