English

Co-evolution of cooperation and resource allocation in the advantageous environment-based spatial multi-game using adaptive control

Physics and Society 2025-04-15 v2

Abstract

In real-life complex systems, individuals often encounter multiple social dilemmas that cannot be effectively captured using a single-game model. Furthermore, the environment and limited resources both play a crucial role in shaping individuals' decision-making behaviors. In this study, we employ an adaptive control mechanism by which agents may benefit from their environment, thus redefining their individual fitness. Under this setting, a detailed examination of the co-evolution of individual strategies and resource allocation is carried. Through extensive simulations, we find that the advantageous environment mechanism not only significantly increases the proportion of cooperators in the system but also influences the resource distribution among individuals. Additionally, limited resources reinforce cooperative behaviors within the system while shaping the evolutionary dynamics and strategic interactions across different dilemmas. Once the system reaches equilibrium, resource distribution becomes highly imbalanced. To promote fairer resource allocation, we introduce a minimum resource guarantee mechanism. Our results show that this mechanism not only reduces disparities in resource distribution across the entire system and among individuals in different dilemmas but also significantly enhances cooperative behavior in higher resource intervals. Finally, to assess the robustness of our model, we further examine the influence of the advantageous environment on system-wide cooperation in small-world and random graph network models.

Keywords

Cite

@article{arxiv.2504.06112,
  title  = {Co-evolution of cooperation and resource allocation in the advantageous environment-based spatial multi-game using adaptive control},
  author = {Chengbin Sun and Alfonso de Miguel-Arribas and Chaoqian Wang and Haoxiang Xia and Yamir Moreno},
  journal= {arXiv preprint arXiv:2504.06112},
  year   = {2025}
}

Comments

30 pages, 18 figures

R2 v1 2026-06-28T22:50:58.851Z