EAGER: Developing dynamic network-based movement models to explore collective decision-making

EAGER：开发基于动态网络的运动模型来探索集体决策

• 批准号: 1250895
• 负责人: Margaret Crofoot
• 金额: $ 15.08万
• 依托单位: Smithsonian Institution
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-01-01 至 2017-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1250895&HistoricalAwards=false
• 关键词: EAGER; Developing; dynamic; network; based

How do groups of individuals reach a consensus about where to go and what to do? Collective decisions like these are one of the great challenges of group-living, and how group members mitigate conflicts of interest is central to understanding the evolution of complex social systems. Social connections among group-mates likely influence how collective decisions are made, but existing models generally assume that these relationships are undifferentiated. A new analytical framework to explore how differentiated social relationships impact collective decision-making is needed. Recent advances in the analysis of dynamic networks provide a powerful new approach to quantifying how relationships change over time. By combining the distinct sets of expertise of the PI and Co-PI, the proposed research will build on these advances to generate novel dynamic network-based collective movement models. Unique, high-resolution GPS tracking data from members of an entire baboon troop will be used to validate these models and to test existing theory about the relative importance of democratic vs. despotic decision making. The dynamic network-based movement models that are developed will be made freely available to the scientific community and should provide a flexible analytical platform for addressing similar questions in a wide range of allied disciplines. The activities supported by this award will provide training in network analysis to U.S. and Panamanian students via a 3-day workshop at the Smithsonian Tropical Research Institute. The project will also contribute to the interdisciplinary training of a post-doctoral researcher, potentiate collaborative research between two female researchers in STEM fields, and provide support for an early career scientist.

一群人如何就去哪里和做什么达成共识？像这样的集体决策是群体生活的巨大挑战之一，而群体成员如何缓解利益冲突是理解复杂社会系统进化的核心。群体成员之间的社会关系可能会影响集体决策的制定，但现有模型通常假设这些关系是无差别的。需要一个新的分析框架来探索不同的社会关系如何影响集体决策。动态网络分析的最新进展为量化关系如何随时间变化提供了一种强有力的新方法。通过结合PI和Co-PI的不同专业知识，拟议的研究将建立在这些进步的基础上，以产生新的动态的基于网络的集体运动模型。来自整个狒狒群体成员的独特的高分辨率GPS跟踪数据将用于验证这些模型，并测试有关民主与专制决策相对重要性的现有理论。开发的基于网络的动态运动模型将免费提供给科学界，并应提供一个灵活的分析平台，用于解决广泛相关学科中的类似问题。该奖项支持的活动将通过在史密森尼热带研究所举办的为期三天的研讨会，为美国和巴拿马的学生提供网络分析方面的培训。该项目还将为一名博士后的跨学科培训做出贡献，促进两名女性研究人员在STEM领域的合作研究，并为一名早期职业科学家提供支持。