EFX存在三个代理

IF 2.3 2区 计算机科学 Q2 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE
Journal of the ACM Pub Date : 2023-09-04 DOI:10.1145/3616009
B. Chaudhury, J. Garg, Kurt Mehlhorn
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引用次数: 0

摘要

研究了一组不可分割的商品在具有可加价值的代理之间公平分配的问题。所考虑的公平概念是无嫉妒(EFX)。尽管许多研究人员多年来作出了重大努力,但除了两种药剂的简单情况外,EFX分配的存在尚未得到解决。本文建设性地证明了三个agent的EFX分配总是存在的。此外,我们通过展示一个具有三个代理的实例来证伪Caragiannis等人[9]的猜想,其中部分EFX分配(某些商品未分配)具有比任何完全EFX分配更高的纳什福利。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
EFX Exists for Three Agents
We study the problem of distributing a set of indivisible goods among agents with additive valuations in a fair manner. The fairness notion under consideration is envy-freeness up to any good (EFX). Despite significant efforts by many researchers for several years, the existence of EFX allocations has not been settled beyond the simple case of two agents. In this paper, we show constructively that an EFX allocation always exists for three agents. Furthermore, we falsify the conjecture of Caragiannis et al. [9] by showing an instance with three agents for which there is a partial EFX allocation (some goods are not allocated) with higher Nash welfare than that of any complete EFX allocation.
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来源期刊
Journal of the ACM
Journal of the ACM 工程技术-计算机:理论方法
CiteScore
7.50
自引率
0.00%
发文量
51
审稿时长
3 months
期刊介绍: The best indicator of the scope of the journal is provided by the areas covered by its Editorial Board. These areas change from time to time, as the field evolves. The following areas are currently covered by a member of the Editorial Board: Algorithms and Combinatorial Optimization; Algorithms and Data Structures; Algorithms, Combinatorial Optimization, and Games; Artificial Intelligence; Complexity Theory; Computational Biology; Computational Geometry; Computer Graphics and Computer Vision; Computer-Aided Verification; Cryptography and Security; Cyber-Physical, Embedded, and Real-Time Systems; Database Systems and Theory; Distributed Computing; Economics and Computation; Information Theory; Logic and Computation; Logic, Algorithms, and Complexity; Machine Learning and Computational Learning Theory; Networking; Parallel Computing and Architecture; Programming Languages; Quantum Computing; Randomized Algorithms and Probabilistic Analysis of Algorithms; Scientific Computing and High Performance Computing; Software Engineering; Web Algorithms and Data Mining
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