The game dynamics of social interaction: Algorithms and applications

社交互动的博弈动力学：算法与应用

• 批准号: 0915145
• 负责人: Andrea Montanari
• 金额: $ 49.98万
• 依托单位: Stanford University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-15 至 2013-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0915145&HistoricalAwards=false
• 关键词: game; dynamics; social; interaction; Algorithms

This project aims at developing mathematical models to describe the dynamics of large populations of interacting strategic agents. Detailed data concerning such phenomena are becoming increasingly available thanks to the unprecedented success of online social networks. Game-theoretic models provide a flexible mathematical framework and Nash equilibria should describe the long term behavior of such models. This research addresses several fundamental problems with this approach: Which of multiple Nash equilibria is selected? How rapidly does a system converge to such an equilibrium? How can one influence these dynamics? Leveraging recent advances in theoretical computer science, efficient algorithms will be developed to answer such questions.The expression "social network" refers to a population of individuals together with their one-to-one social relationships (which can be of personal or economic nature). It is clear that the structure of such a network deeply affects the behavior of society as a whole (in particular, from the economic point of view). This intuition has never become practical or quantitative due to the lack of detailed data on the structure and dynamics of social networks. The Internet, and in particular the success of online social networking is dramatically changing this situation. This project aims at developing mathematical models and algorithms urgently needed to harness this data explosion. It will open the way to the application of economic analysis tools to this new arena, and thus facilitate new ways of exploiting online networks.

该项目旨在开发数学模型来描述大量相互作用的战略代理的动态。 由于在线社交网络的空前成功，有关此类现象的详细数据变得越来越可用。 博弈论模型提供了灵活的数学框架，纳什均衡应该描述此类模型的长期行为。 这项研究解决了这种方法的几个基本问​​题：选择多个纳什均衡中的哪一个？ 系统收敛到这种平衡的速度有多快？ 如何影响这些动态？ 利用理论计算机科学的最新进展，将开发有效的算法来回答此类问题。“社交网络”一词是指一群个体及其一对一的社会关系（可以是个人或经济性质） 。 显然，这种网络的结构深刻地影响着整个社会的行为（特别是从经济角度来看）。 由于缺乏有关社交网络结构和动态的详细数据，这种直觉从未变得实用或定量。 互联网，特别是在线社交网络的成功正在极大地改变这种情况。 该项目旨在开发利用这种数据爆炸急需的数学模型和算法。 它将为经济分析工具在这个新领域的应用开辟道路，从而促进利用在线网络的新方法。