ICES: Small: Contribution Games in Social Networks

这个项目的重点是网络形成的自利代理人。具体来说，它研究了社交网络中的贡献博弈，其中玩家/节点不仅与其他人形成联系/关系，而且还决定了他们联系的强度。本计画将分析平衡解的品质、局部动态的收敛特性，以及改善这些特性的机制。这项工作将导致有效的算法计算各种合理的贡献游戏的结果，和算法“轻推”的球员，以形成更好的结果，给他们小的激励，使用近似算法，否则棘手的问题。具体而言，本研究将考虑以下主题。(1)分析网络贡献游戏的模型，该模型捕捉了玩家优化其本地关系的本质。纳什均衡等概念对这类模型的用处有限，因此该项目转而关注成对均衡、强均衡和收敛动态。 (2)一般贡献博弈是网络贡献博弈的一个重要扩展：参与者为多人项目做出贡献，而不是两两关系。(3)中心性、友谊和利他主义。除了希望最大化参与者参与的所有项目/关系的总体成功之外，他们还可能希望形成使他们在社交网络中处于良好位置的连接，因此试图最大化一些“中心性”的概念，或者他们可能关心整个网络的质量，就像在具有公共物品的游戏中一样。本项目将分析博弈中参与者的效用是这些考虑的组合，并根据参与者效用函数的类型得出均衡解的结构和质量的一般结果。社交网络渗透到人类生活的大多数方面，影响着从流行病的传播到找工作的能力的一切。既然社交网络数据的收集变得越来越容易，了解社交网络形成的结构、属性和激励因素已成为一个重要的研究课题。通过明确考虑社会网络中的联系强度，而不仅仅是它们的存在，这项工作将为社交网络的博弈论模型增加一个新的维度，并获得对参与者行为和社交网络结构的新见解。这项工作也可能提出有效的方法来“轻推”社会网络的参与者，以形成更好的结果，给他们一些小的激励。此外，该项目将为分析有限共谋系统提供新技术。对贡献博弈的研究表明，参与者除了关注局部成功外，还关注中心性、友谊和利他主义，这将是理解在这种玩家激励组合下社交网络结构的第一次重大尝试。该项目将包括与从事社交网络研究的理论和应用研究人员的合作，包括来自复杂系统、流行病学、社会学和管理学院的研究人员。由于对社交网络的广泛兴趣，该项目可能会激发上述许多领域的新方法。最后，这项研究将得到PI教育计划的大力支持，该计划包括教授几门带有研究内容的课程，就此主题举办研讨会，并招募几名研究生和本科生参与该项目。

This project focuses on network formation by self-interested agents. Specifically, it studies contribution games in social networks, where players/nodes not only form connections/relationships with others, but also determine the intensity of their connections. This project will analyze the quality of equilibrium solutions, convergence properties of local dynamics, and mechanisms to improve these properties. This work will result in efficient algorithms for computing various reasonable outcomes of contribution games, and algorithms for "nudging" the players to form better outcomes by giving them small incentives, using approximation algorithms for otherwise intractable problems. More concretely, this research will consider the following topics. (1) Analyzing a model of Network Contribution Games that captures the essence of players optimizing their local relationships. Concepts such as Nash equilibrium are of limited usefulness for such models, so the project instead focuses on pairwise equilibrium, strong equilibrium, and convergence dynamics. (2) General Contribution Games are an important extension of network contribution games: instead of pairwise relationships, players contribute to many-person projects. (3) Centrality, Friendship, and Altruism. Other than the desire to maximize total success of all projects/relationships players are involved in, they may also desire to form connections that make them well-positioned in the social network, and so attempt to maximize some notion of "centrality" or they may care about the quality of the network as a whole, as in games with public goods. This project will analyze games where the utility of a player is a combination of such considerations, and derive general results on the structure and quality of equilibrium solutions depending on the types of player utility functions.Social networks pervade most aspects of human life, and affect everything from the spread of epidemics to the ability to find a job. Now that data on social networks has become easier to collect, understanding the structure, properties, and incentives of social network formation has become a crucial research topic. By explicitly taking into account the strength of bonds in a social network, and not just their existence, this work will add a new dimension to game-theoretic models of social networks, and obtain new insight into participant behavior, and into the structure of social networks. This work may also suggest efficient methods for "nudging" the participants of a social network to form better outcomes by giving them small incentives. In addition, this project will contribute new techniques for analyzing systems with limited collusion. The study of contribution games where participants care about centrality, friendship, and altruism in addition to their local success, will be the first major attempt to understand the structure of social networks under such a combination of player incentives. This project will include collaborations with both theoretical and applied researchers working on social networks, including researchers from complex systems, epidemiology, sociology, and the school of management. Because of wide-spread interest in social networks, this project may inspire new approaches in many of the fields mentioned above. Finally, this research will be strongly complimented by the PI's education plan, which includes teaching several courses with research components, forming a workshop on this topic, and recruiting several graduate and undergraduate students to work on this project.