On Dynamics of Basic Network Creation Games With Non-Uniform Communication Interest

IF 1.5 4区 计算机科学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Maxime Dresler, Sanaï Mansour, Safaâ Talhaoui, Yukiko Yamauchi, Sébastien Tixeuil
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引用次数: 0

Abstract

We consider the network construction process by selfish players. Each player is associated with a vertex of a communication graph and can simultaneously remove one incident edge and add a new incident edge. Each player is interested in a subset of players and the goal of each player is to minimize the average or maximum distance to these players. Starting from a given initial communication graph, a sequence of selfish edge swaps generates an evolution of the communication graph. Due to non-uniform communication interest, this game may converge to a disconnected Nash equilibrium, which may attain infinite social costs. In this paper, we focus on the dynamics of this game. We first give theoretical analysis such as the existence of a best response cycle and a sufficient condition for keeping connectivity in dynamics. We then present simulation results to show the ratio of Nash equilibria with infinite cost, diameters of Nash equilibria, social cost, price of anarchy, price of stability, and convergence time.

基于非均匀传播兴趣的基础网络创造游戏动力学研究
我们考虑自私玩家的网络建设过程。每个玩家都与通信图的一个顶点相关联,并且可以同时删除一个事件边并添加一个新的事件边。每个玩家都对玩家的一个子集感兴趣,每个玩家的目标是最小化与这些玩家的平均或最大距离。从给定的初始通信图开始,一系列自利边交换生成通信图的进化。由于交流兴趣的不均匀性,博弈可能会收敛到一个不连贯的纳什均衡,从而获得无限的社会成本。在本文中,我们将着眼于这一游戏的动态。首先给出了最佳响应周期的存在性和保持动态连通性的充分条件等理论分析。然后,我们给出了模拟结果,以显示具有无限成本的纳什均衡的比率,纳什均衡的直径,社会成本,无政府状态的价格,稳定的价格和收敛时间。
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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来源期刊
Concurrency and Computation-Practice & Experience
Concurrency and Computation-Practice & Experience 工程技术-计算机:理论方法
CiteScore
5.00
自引率
10.00%
发文量
664
审稿时长
9.6 months
期刊介绍: Concurrency and Computation: Practice and Experience (CCPE) publishes high-quality, original research papers, and authoritative research review papers, in the overlapping fields of: Parallel and distributed computing; High-performance computing; Computational and data science; Artificial intelligence and machine learning; Big data applications, algorithms, and systems; Network science; Ontologies and semantics; Security and privacy; Cloud/edge/fog computing; Green computing; and Quantum computing.
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