论文标题
优先游戏中的本地聚合
Local Aggregation in Preference Games
论文作者
论文摘要
在这项工作中，我们介绍了代理商在社交网络中的新决策模型。代理人对策略有天生的偏好，但是由于社会互动，代理人的决定不仅受其先天偏好的影响，而且还受其社会邻国做出的决定。我们假设代理的策略嵌入到{近似}度量空间中。此外，与以前的文献不同，我们假设由于缺乏信息，每个代理在本地通过汇总值代表网络的趋势，可以将其解释为聚合函数的输出。我们回答了一些与纯纳什均衡的存在和效率有关的基本问题。
In this work we introduce a new model of decision-making by agents in a social network. Agents have innate preferences over the strategies but, because of the social interactions, the decision of the agents are not only affected by their innate preferences but also by the decision taken by their social neighbors. We assume that the strategies of the agents are embedded in an {approximate} metric space. Furthermore, departing from the previous literature, we assume that, due to the lack of information, each agent locally represents the trend of the network through an aggregate value, which can be interpreted as the output of an aggregation function. We answer some fundamental questions related to the existence and efficiency of pure Nash equilibria.
