基于时间序列的复杂运动领导动力推断框架
Framework for Inferring Leadership Dynamics of Complex Movement from Time Series
摘要：
领导力在社会性动物（包括人类）的协调活动（如狩猎、迁徙、体育运动、外交谈判等）中起着关键的决策和凝聚作用。在这些协调活动中，领导力是组织成员之间的互动，使群体实现集体目标的过程。了解协调活动的启动使科学家能够更深入地了解社会物种的行为。然而，通过仅使用时间序列的活动数据，推断领导所表现出的协调活动的启动面临着许多挑战性的问题。首先，协调活动是动态的，并随着时间的推移而变化。第二，若干不同的协调活动可能在各分组之间同时进行。第三，没有基本的概念来描述这些活动的计算。在本文中，我们形式化的派系发起人推理问题，并提出了一个领导推理框架作为解决这个问题。该框架没有对领导者的特征或协调过程的参数做出任何假设。该框架在模拟和生物数据集（鱼群）中的表现都优于我们的非平凡基线。此外，我们展示了应用我们的框架作为一种工具，研究组合并和分裂动力学的另一个生物数据集的野生狒狒的轨迹。此外，我们的问题形式化和框架使科学家有机会分析协调的活动，并产生关于集体行为的科学假设，这些假设可以在统计和现场进行测试。
英文摘要：
Leadership plays a key role in social animals, including humans, decision-making and coalescence in coordinated activities such as hunting, migration, sport, diplomatic negotiation etc. In these coordinated activities, leadership is a process that organizes interactions among members to make a group achieve collective goals. Understanding initiation of coordinated activities allows scientists to gain more insight into social species behaviors. However, by using only time series of activities data, inferring leadership as manifested by the initiation of coordinated activities faces many challenging issues. First, coordinated activities are dynamic and are changing over time. Second, several different coordinated activities might occur simultaneously among subgroups. Third, there is no fundamental concept to describe these activities computationally. In this paper, we formalize Faction Initiator Inference Problem and propose a leadership inference framework as a solution of this problem. The framework makes no assumption about the characteristics of a leader or the parameters of the coordination process. The framework performs better than our non-trivial baseline in both simulated and biological datasets (schools of fish). Moreover, we demonstrate the application of our framework as a tool to study group merging and splitting dynamics on another biological dataset of trajectories of wild baboons. In addition, our problem formalization and framework enable opportunities for scientists to analyze coordinated activities and generate scientific hypotheses about collective behaviors that can be tested statistically and in the field.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
