Xingyu Pan, Zerong Guo

Chaos, Solitons & Fractals
Volume 196, July 2025, 116369

Many real-world systems comprise fundamental elements that exhibit mutual exclusion and alternating activation. Here, we develop a framework for the evolution of network structures that captures the behaviors of such systems. We define the dynamic resilience of temporal networks using variational rates to measure how the evolutionary trajectories of network structures diverge under perturbations. We show that perturbations to specific edges and states of mutually exclusive elements can cause evolutionary trajectories of network structures to deviate significantly from the original path. Furthermore, we demonstrate that traditional resilience factors do not affect dynamic resilience, which is instead governed by mutual exclusion within our framework. Our results advance the study of network resilience, particularly for networks with evolving structures, offering a novel perspective for identifying crucial perturbations within the context of the states of mutually exclusive elements.

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Chengbin Sun, Alfonso de Miguel-Arribas, Chaoqian Wang, Haoxiang Xia, Yamir Moreno

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.

Read the full article at: arxiv.org