有不确定权重问题的可能赢家

IF 1.1 3区 计算机科学 Q1 BUSINESS, FINANCE
Dorothea Baumeister , Marc Neveling , Magnus Roos , Jörg Rothe , Lena Schend , Robin Weishaupt , Lirong Xia
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引用次数: 1

摘要

最初的可能赢家问题包括一个具有部分偏好的未加权选举和一个杰出的候选人c,并询问偏好是否可以扩展到总偏好,以便c赢得给定的选举。我们引入了这个问题的一个新的变体:权重不确定的可能赢家。在这种变体中,对于给定的加权选举,不是某些偏好,而是某些偏好的权重是不确定的。我们引入了一个研究非负整数和有理权问题的一般框架,以及问题本身的四种不同变体:有和没有给定的总权上界,有和没有指定的范围来选择权。我们研究了重要投票系统的这些问题的复杂性,如评分协议、(简化的)巴克林和后备投票、具有决选权的多数票和具有决选的否决权、Copelandα、排名对和Borda。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The possible winner with uncertain weights problem

The original possible winner problem consists of an unweighted election with partial preferences and a distinguished candidate c and asks whether the preferences can be extended to total ones such that c wins the given election. We introduce a novel variant of this problem: possible winner with uncertain weights. In this variant, for a given weighted election, not some of the preferences but some of the preferences' weights are uncertain. We introduce a general framework to study this problem for nonnegative integer and rational weights as well as for four different variations of the problem itself: with and without given upper bounds on the total weight and with and without given ranges to choose weights from. We study the complexity of these problems for important voting systems such as scoring protocols, (simplified) Bucklin and fallback voting, plurality with runoff and veto with runoff, Copelandα, ranked pairs, and Borda.

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来源期刊
Journal of Computer and System Sciences
Journal of Computer and System Sciences 工程技术-计算机:理论方法
CiteScore
3.70
自引率
0.00%
发文量
58
审稿时长
68 days
期刊介绍: The Journal of Computer and System Sciences publishes original research papers in computer science and related subjects in system science, with attention to the relevant mathematical theory. Applications-oriented papers may also be accepted and they are expected to contain deep analytic evaluation of the proposed solutions. Research areas include traditional subjects such as: • Theory of algorithms and computability • Formal languages • Automata theory Contemporary subjects such as: • Complexity theory • Algorithmic Complexity • Parallel & distributed computing • Computer networks • Neural networks • Computational learning theory • Database theory & practice • Computer modeling of complex systems • Security and Privacy.
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