网络上聚类博弈无序代价的拓扑界

IF 1.1 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS ACM Transactions on Economics and Computation Pub Date : 2023-10-09 DOI:10.1145/3625689
Pieter Kleer, Guido Schäfer
{"title":"网络上聚类博弈无序代价的拓扑界","authors":"Pieter Kleer, Guido Schäfer","doi":"10.1145/3625689","DOIUrl":null,"url":null,"abstract":"We consider clustering games in which the players are embedded into a network and want to coordinate (or anti-coordinate) their strategy with their neighbors. The goal of a player is to choose a strategy that maximizes her utility given the strategies of her neighbors. Recent studies show that even very basic variants of these games exhibit a large Price of Anarchy: A large inefficiency between the total utility generated in centralized outcomes and equilibrium outcomes in which players selfishly maximize their utility. Our main goal is to understand how structural properties of the network topology impact the inefficiency of these games. We derive topological bounds on the Price of Anarchy for different classes of clustering games. These topological bounds provide a more informative assessment of the inefficiency of these games than the corresponding worst-case Price of Anarchy bounds. More specifically, depending on the type of clustering game, our bounds reveal that the Price of Anarchy depends on the maximum subgraph density or the maximum degree of the graph. Among others, these bounds enable us to derive bounds on the Price of Anarchy for clustering games on Erdős-Rényi random graphs. Depending on the graph density, these bounds stand in stark contrast to the known worst-case Price of Anarchy bounds. Additionally, we also characterize the set of distribution rules that guarantee the existence of a pure Nash equilibrium or the convergence of best-response dynamics. These results are of a similar spirit as the work of Gopalakrishnan et al. [19] and complement work of Anshelevich and Sekar [4].","PeriodicalId":42216,"journal":{"name":"ACM Transactions on Economics and Computation","volume":null,"pages":null},"PeriodicalIF":1.1000,"publicationDate":"2023-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Topological Bounds on the Price of Anarchy of Clustering Games on Networks\",\"authors\":\"Pieter Kleer, Guido Schäfer\",\"doi\":\"10.1145/3625689\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We consider clustering games in which the players are embedded into a network and want to coordinate (or anti-coordinate) their strategy with their neighbors. The goal of a player is to choose a strategy that maximizes her utility given the strategies of her neighbors. Recent studies show that even very basic variants of these games exhibit a large Price of Anarchy: A large inefficiency between the total utility generated in centralized outcomes and equilibrium outcomes in which players selfishly maximize their utility. Our main goal is to understand how structural properties of the network topology impact the inefficiency of these games. We derive topological bounds on the Price of Anarchy for different classes of clustering games. These topological bounds provide a more informative assessment of the inefficiency of these games than the corresponding worst-case Price of Anarchy bounds. More specifically, depending on the type of clustering game, our bounds reveal that the Price of Anarchy depends on the maximum subgraph density or the maximum degree of the graph. Among others, these bounds enable us to derive bounds on the Price of Anarchy for clustering games on Erdős-Rényi random graphs. Depending on the graph density, these bounds stand in stark contrast to the known worst-case Price of Anarchy bounds. Additionally, we also characterize the set of distribution rules that guarantee the existence of a pure Nash equilibrium or the convergence of best-response dynamics. These results are of a similar spirit as the work of Gopalakrishnan et al. [19] and complement work of Anshelevich and Sekar [4].\",\"PeriodicalId\":42216,\"journal\":{\"name\":\"ACM Transactions on Economics and Computation\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.1000,\"publicationDate\":\"2023-10-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Transactions on Economics and Computation\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3625689\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Transactions on Economics and Computation","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3625689","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

摘要

我们考虑聚类博弈,其中参与者嵌入到网络中,并希望与邻居协调(或反协调)他们的策略。玩家的目标是根据邻居的策略选择一种能最大化自己效用的策略。最近的研究表明,即使是这些游戏的基本变体也表现出了巨大的无政府价格(Price of Anarchy):集中结果所产生的总效用与玩家自私地最大化其效用的均衡结果之间存在巨大的效率低下。我们的主要目标是了解网络拓扑的结构属性如何影响这些游戏的低效率。我们推导了不同类别聚类对策的无序价格的拓扑界。这些拓扑边界比相应的最坏情况下的无政府状态价格边界提供了对这些博弈的低效率的更有价值的评估。更具体地说,根据聚类博弈的类型,我们的边界揭示了无政府状态的代价取决于最大子图密度或图的最大程度。除此之外,这些界限使我们能够推导出Erdős-Rényi随机图上聚类游戏的混乱价格的界限。根据图密度的不同,这些边界与已知的最坏情况下的无政府状态边界形成鲜明对比。此外,我们还描述了保证纯纳什均衡存在或最佳响应动力学收敛的一组分布规则。这些结果与Gopalakrishnan等人的工作具有相似的精神,并补充了Anshelevich和Sekar等人的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Topological Bounds on the Price of Anarchy of Clustering Games on Networks
We consider clustering games in which the players are embedded into a network and want to coordinate (or anti-coordinate) their strategy with their neighbors. The goal of a player is to choose a strategy that maximizes her utility given the strategies of her neighbors. Recent studies show that even very basic variants of these games exhibit a large Price of Anarchy: A large inefficiency between the total utility generated in centralized outcomes and equilibrium outcomes in which players selfishly maximize their utility. Our main goal is to understand how structural properties of the network topology impact the inefficiency of these games. We derive topological bounds on the Price of Anarchy for different classes of clustering games. These topological bounds provide a more informative assessment of the inefficiency of these games than the corresponding worst-case Price of Anarchy bounds. More specifically, depending on the type of clustering game, our bounds reveal that the Price of Anarchy depends on the maximum subgraph density or the maximum degree of the graph. Among others, these bounds enable us to derive bounds on the Price of Anarchy for clustering games on Erdős-Rényi random graphs. Depending on the graph density, these bounds stand in stark contrast to the known worst-case Price of Anarchy bounds. Additionally, we also characterize the set of distribution rules that guarantee the existence of a pure Nash equilibrium or the convergence of best-response dynamics. These results are of a similar spirit as the work of Gopalakrishnan et al. [19] and complement work of Anshelevich and Sekar [4].
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
ACM Transactions on Economics and Computation
ACM Transactions on Economics and Computation COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS-
CiteScore
3.80
自引率
0.00%
发文量
11
期刊介绍: The ACM Transactions on Economics and Computation welcomes submissions of the highest quality that concern the intersection of computer science and economics. Of interest to the journal is any topic relevant to both economists and computer scientists, including but not limited to the following: Agents in networks Algorithmic game theory Computation of equilibria Computational social choice Cost of strategic behavior and cost of decentralization ("price of anarchy") Design and analysis of electronic markets Economics of computational advertising Electronic commerce Learning in games and markets Mechanism design Paid search auctions Privacy Recommendation / reputation / trust systems Systems resilient against malicious agents.
期刊最新文献
Convexity in Real-time Bidding and Related Problems Matching Tasks and Workers under Known Arrival Distributions: Online Task Assignment with Two-sided Arrivals Blockchain-Based Decentralized Reward Sharing: The case of mining pools Editorial from the New Co-Editors-in-Chief of ACM Transactions on Economics and Computation Price of Anarchy in Algorithmic Matching of Romantic Partners
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1