Truthful and Stable One-sided Matching on Networks

	Truthful and Stable One-sided Matching on Networks
	Yang, Tianyi; Zhai, Yuxiang; Zhao, Dengji; Song, Xinwei; Li, Miao
	2023-12
会议录名称	2024 INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS
ISSN	1548-8403
卷号	2024-May
页码	2564-2566
发表状态	正式接收
摘要	Diffusion one-sided matching aims at incentivizing more participants to match so as to improve overall matching result. Existing works have tried to add constraints on Top Trading Cycles to obtain the incentive, but it only works in trees. In this paper, we first propose a mechanism named Swap With Neighbors (SWN), which can work in any graph structure and intuitively satisfy incentive compatibility and the tightest stability (first defined here) in the new setting. Then we find a natural improvement of SWN called Leave and Share which not only reaches the same properties as SWN but also provides an obvious efficiency difference. © 2024 International Foundation for Autonomous Agents and Multiagent Systems.
会议录编者/会议主办者	Artificial Intelligence ; Autonomous Agents and Multi-Agent Systems ; et al. ; NSF ; University of Auckland ; University of Auckland, School of Computer Science
关键词	Autonomous agents Graph structures Incentive compatibility Invitation incentive Matchings Mechanism design Property Top trading cycle
会议名称	23rd International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2024
会议地点	Auckland, New zealand
会议日期	May 6, 2024 - May 10, 2024
收录类别	EI
语种	英语
出版者	International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
EI入藏号	20242516292519
EI主题词	Multi agent systems
EISSN	1558-2914
原始文献类型	Conference article (CA)
文献类型	会议论文
条目标识符	https://kms.shanghaitech.edu.cn/handle/2MSLDSTB/378360
专题	信息科学与技术学院_硕士生信息科学与技术学院_PI研究组_赵登吉组
通讯作者	Yang, Tianyi; Zhao, Dengji
作者单位	ShanghaiTech University
第一作者单位	上海科技大学
通讯作者单位	上海科技大学
第一作者的第一单位	上海科技大学
推荐引用方式 GB/T 7714	Yang, Tianyi,Zhai, Yuxiang,Zhao, Dengji,et al. Truthful and Stable One-sided Matching on Networks[C]//Artificial Intelligence, Autonomous Agents and Multi-Agent Systems, et al., NSF, University of Auckland, University of Auckland, School of Computer Science:International Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS),2023:2564-2566.