{"title":"Beyond Proportional Individual Guarantees for Binary Perpetual Voting","authors":"Yotam Gafni, Ben Golan","doi":"arxiv-2408.08767","DOIUrl":null,"url":null,"abstract":"Perpetual voting studies fair collective decision-making in settings where\nmany decisions are to be made, and is a natural framework for settings such as\nparliaments and the running of blockchain Decentralized Autonomous\nOrganizations (DAOs). We focus our attention on the binary case (YES/NO\ndecisions) and \\textit{individual} guarantees for each of the participating\nagents. We introduce a novel notion, inspired by the popular maxi-min-share\n(MMS) for fair allocation. The agent expects to get as many decisions as if\nthey were to optimally partition the decisions among the agents, with an\nadversary deciding which of the agents decides on what bundle. We show an\nonline algorithm that guarantees the MMS notion for $n=3$ agents, an offline\nalgorithm for $n=4$ agents, and show that no online algorithm can guarantee the\n$MMS^{adapt}$ for $n\\geq 7$ agents. We also show that the Maximum Nash Welfare\n(MNW) outcome can only guarantee $O(\\frac{1}{n})$ of the MMS notion in the\nworst case.","PeriodicalId":501316,"journal":{"name":"arXiv - CS - Computer Science and Game Theory","volume":"43 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-08-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - CS - Computer Science and Game Theory","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2408.08767","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Perpetual voting studies fair collective decision-making in settings where
many decisions are to be made, and is a natural framework for settings such as
parliaments and the running of blockchain Decentralized Autonomous
Organizations (DAOs). We focus our attention on the binary case (YES/NO
decisions) and \textit{individual} guarantees for each of the participating
agents. We introduce a novel notion, inspired by the popular maxi-min-share
(MMS) for fair allocation. The agent expects to get as many decisions as if
they were to optimally partition the decisions among the agents, with an
adversary deciding which of the agents decides on what bundle. We show an
online algorithm that guarantees the MMS notion for $n=3$ agents, an offline
algorithm for $n=4$ agents, and show that no online algorithm can guarantee the
$MMS^{adapt}$ for $n\geq 7$ agents. We also show that the Maximum Nash Welfare
(MNW) outcome can only guarantee $O(\frac{1}{n})$ of the MMS notion in the
worst case.