A common generalization of budget games and congestion games

IF 0.9 4区 数学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
Fuga Kiyosue, Kenjiro Takazawa
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引用次数: 0

Abstract

Budget games were introduced by Drees, Riechers, and Skopalik (2014) as a model of noncooperative games arising from resource allocation problems. Budget games have several similarities to congestion games, one of which is that the matroid structure of the strategy space is essential for the existence of a pure Nash equilibrium (PNE). Despite these similarities, however, the theoretical relation between budget games and congestion games has been unclear. In this paper, we provide a common generalization of budget games and congestion games, called generalized budget games (g-budget games, for short), to establish a large class of noncooperative games retaining the nice property of the matroid structure. We show that the model of g-budget games includes weighted congestion games and player-specific congestion games under certain assumptions. We further show that g-budget games also include offset budget games, a generalized model of budget games by Drees, Feldotto, Riechers, and Skopalik (2019). We then prove that every matroid g-budget game has a PNE, which extends the result for budget games. We finally a PNE in a certain class of singleton g-budget games can be computed in a greedy manner.

预算博弈和拥挤博弈的共同概括
预算博弈由 Drees、Riechers 和 Skopalik(2014 年)提出,是资源分配问题中产生的一种非合作博弈模型。预算博弈与拥挤博弈有几处相似之处,其中之一就是策略空间的矩阵结构对于纯纳什均衡(PNE)的存在至关重要。然而,尽管有这些相似之处,预算博弈与拥堵博弈之间的理论关系却一直不清晰。在本文中,我们对预算博弈和拥挤博弈进行了共同的概括,称为广义预算博弈(简称 g-budget 博弈),从而建立了一大类保留了矩阵结构这一良好特性的非合作博弈。我们证明,在某些假设条件下,g-预算博弈模型包括加权拥塞博弈和特定玩家拥塞博弈。我们进一步证明,g 预算博弈还包括抵消预算博弈,这是 Drees、Feldotto、Riechers 和 Skopalik(2019 年)提出的预算博弈的广义模型。然后,我们证明了每个矩阵 g-budget 博弈都有一个 PNE,这扩展了预算博弈的结果。最后,我们可以用贪婪的方法计算某类单子 g-budget 博弈中的 PNE。
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
Journal of Combinatorial Optimization
Journal of Combinatorial Optimization 数学-计算机:跨学科应用
CiteScore
2.00
自引率
10.00%
发文量
83
审稿时长
6 months
期刊介绍: The objective of Journal of Combinatorial Optimization is to advance and promote the theory and applications of combinatorial optimization, which is an area of research at the intersection of applied mathematics, computer science, and operations research and which overlaps with many other areas such as computation complexity, computational biology, VLSI design, communication networks, and management science. It includes complexity analysis and algorithm design for combinatorial optimization problems, numerical experiments and problem discovery with applications in science and engineering. The Journal of Combinatorial Optimization publishes refereed papers dealing with all theoretical, computational and applied aspects of combinatorial optimization. It also publishes reviews of appropriate books and special issues of journals.
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