Mean Field Games in Nudge Systems for Societal Networks

Jian Li, Bainan Xia, Xinbo Geng, Hao Ming, S. Shakkottai, V. Subramanian, Le Xie
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引用次数: 12

Abstract

We consider the general problem of resource sharing in societal networks, consisting of interconnected communication, transportation, energy, and other networks important to the functioning of society. Participants in such network need to take decisions daily, both on the quantity of resources to use as well as the periods of usage. With this in mind, we discuss the problem of incentivizing users to behave in such a way that society as a whole benefits. To perceive societal level impact, such incentives may take the form of rewarding users with lottery tickets based on good behavior and periodically conducting a lottery to translate these tickets into real rewards. We will pose the user decision problem as a mean field game and the incentives question as one of trying to select a good mean field equilibrium (MFE). In such a framework, each agent (a participant in the societal network) takes a decision based on an assumed distribution of actions of his/her competitors and the incentives provided by the social planner. The system is said to be at MFE if the agent’s action is a sample drawn from the assumed distribution. We will show the existence of such an MFE under general settings, and also illustrate how to choose an attractive equilibrium using as an example demand-response in the (smart) electricity network.
社会网络助推系统中的平均场游戏
我们考虑社会网络中资源共享的一般问题,包括相互连接的通信、运输、能源和其他对社会功能重要的网络。这种网络的参与者需要每天做出决定,包括使用资源的数量和使用时间。考虑到这一点,我们将讨论如何激励用户以使整个社会受益的方式行事。为了感知社会层面的影响,这种激励可以采取基于良好行为的奖券奖励用户的形式,并定期进行抽奖,将这些奖券转化为真正的奖励。我们将把用户决策问题作为一个平均场博弈,将激励问题作为一个试图选择一个好的平均场均衡(MFE)的问题。在这样一个框架中,每个代理(社会网络中的参与者)根据假设的竞争对手的行动分布和社会计划者提供的激励来做出决策。如果代理的行为是从假设分布中抽取的样本,则系统被称为MFE。我们将展示在一般设置下存在这样一个MFE,并举例说明如何选择一个有吸引力的均衡,使用(智能)电网中的需求响应作为示例。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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