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arXiv 2103.14847cs.GTcs.CCcs.MA
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不完全信息下基于认可的委员会投票

Approval-Based Committee Voting under Incomplete Information

Aviram Imber, Jonas Israel, Markus Brill, Benny Kimelfeld

AI总结:

该研究针对选民认可偏好不完全的场景,构建多种不完全性模型,分析经典基于认可的委员会投票规则下相关计算问题的复杂度,并探讨比例代表公理与委员会代表性判定问题。

摘要:

我们研究了选民认可偏好信息不完全场景下的基于认可的委员会投票问题。我们考虑了多种不完全性模型,其中每位选民将候选人集合划分为认可、不认可和未知三类,未知类别中的候选人之间可能存在序数偏好约束。这一设定涵盖了选民尚未评估所有候选人,且/或无法确定选民在认可与不认可候选人之间划定阈值的场景。我们针对包括比例认可投票(Proportional Approval Voting)和Chamberlin-Courant规则在内的多种经典基于认可的委员会投票规则,研究了若干基础计算问题的复杂度。这些问题包括判断给定候选人集合是否为可能或必然的获胜委员会,以及给定候选人是否可能或必然属于获胜委员会。我们还探讨了比例代表公理,以及判断给定委员会是否可能或必然具有代表性的问题。

英文摘要:

We investigate approval-based committee voting with incomplete information about the approval preferences of voters. We consider several models of incompleteness where each voter partitions the set of candidates into approved, disapproved, and unknown candidates, possibly with ordinal preference constraints among candidates in the latter category. This captures scenarios where voters have not evaluated all candidates and/or it is unknown where voters draw the threshold between approved and disapproved candidates. We study the complexity of some fundamental computational problems for a number of classic approval-based committee voting rules including Proportional Approval Voting and Chamberlin-Courant. These problems include determining whether a given set of candidates is a possible or necessary winning committee and whether a given candidate is possibly or necessarily a member of the winning committee. We also consider proportional representation axioms and the problem of deciding whether a given committee is possibly or necessarily representative.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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