标题： 社会网络中的行为对齐 显示英文标题

标题： Behavioral alignment in social networks

摘要： 我们在大规模群体中观察到的有序行为，例如鱼群游动和人群的有序移动，既普遍存在，又对这些系统的生存和稳定性至关重要。 这种复杂的集体行为往往源于个体之间简单的局部交互和策略调整。 长期以来，理解这些基本规则如何塑造复杂的群体动力学一直是重要的科学挑战。 历史上，研究主要集中在模仿和社会学习上，在这种情况下，个体通过采纳更成功的同伴的策略来完善自身的行为。 然而，近年来，一种替代性的学习方法——自我探索和内省式学习——引起了越来越多的关注。 在这种范式下，个体评估自己的情况，并选择最符合其特定条件的策略。 这种学习的主要形式有两种：协调和反协调，其中个体分别与当地多数人保持一致或偏离。 在这项研究中，我们分析了协调和反协调个体组成的网络系统，探讨了系统动态、网络结构和行为模式的综合影响。 我们回答了一些实际问题，包括平衡点的数量、它们的特性、平衡时间以及系统的韧性。 我们发现平衡状态的数量可能非常大，甚至随着网络结构的微小变化呈指数增长。 此外，网络结构对平均平衡时间有显著影响。 尽管这些发现复杂，但可以通过一个单一的简单网络特征——平均路径长度来捕捉这些变化。 我们的研究为理解交互结构的修改如何影响社会网络中的行为一致性提供了宝贵的见解。 显示英文摘要

摘要： The orderly behaviors observed in large-scale groups, such as fish schooling and the organized movement of crowds, are both ubiquitous and essential for the survival and stability of these systems. Such complex collective behaviors often emerge from simple local interactions and strategy adjustments among individuals. Understanding how these basic rules shape complex group dynamics has long been a significant scientific challenge. Historically, research has predominantly focused on imitation and social learning, where individuals adopt the strategies of more successful peers to refine their behavior. However, in recent years, an alternative learning approach, self-exploration and introspective learning, has garnered increasing attention. In this paradigm, individuals assess their own circumstances and select strategies that best align with their specific conditions. Two primary forms of this learning are coordination and anti-coordination, where individuals align with and diverge from the local majority, respectively. In this study, we analyze networked systems of coordinating and anti-coordinating individuals, exploring the combined effects of system dynamics, network structure, and behavioral patterns. We address several practical questions, including the number of equilibria, their characteristics, the equilibrium time, and the resilience of systems. We find that the number of equilibrium states can be extremely large, even increasing exponentially with minor alternations to the network structure. Moreover, the network structure has a significant impact on the average equilibrium time. Despite the complexity of these findings, variations can be captured by a single, simple network characteristic: the average path length. Our research offers valuable insights into how modifications to the interaction structure can influence behavioral alignment in social networks.