arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2210.08985cs.CYcs.GT
收藏

选举政府部长

Election of government ministers

Itai Lashover, Liav Weiss, Amichai Kafka, Shoshana Levin

摘要:

行政部门(政府)通常不是由人民直接选举产生的,而是由另一个选举产生的机构或个人,如议会或总统。因此,其成员不直接对人民负责,无论是个人还是团体。我们提出一个方案,政府成员由人民直接选举,并寻求在这个过程中实现比例代表制。我们将提出一个正式的模型来分配K个办公室,每个办公室都与一组不相交的候选人竞争该席位。一组选民为每个办公室提供选票。由于对每个办公室单独使用简单多数投票可能会导致少数人的偏好被完全忽略,因此我们在这里将贪婪版本的比例批准投票(GreedyPAV)应用于我们的框架。在《选举行政部门》一文中,你可以找到对该模型的深入解释,并通过基于计算机的模拟演示了如何使用这一规则一起投票选举所有职位,克服了这一弱点,并维护了比例公理。在这篇文章中,我们将介绍Rutvik Page,Ehud Shapiro和Nimrod Talmon在上述文章中提出的算法(GreedyPAV)的实现。此外,我们还通过一项调查测试了我们的实现,调查结果将在本文后面介绍和分析。

英文摘要:

The executive branch (the government) is usually not directly elected by the people, but is created by another elected body or person such as the parliament or the president. As a result, its members are not directly accountable to the people, individually or as a group. We propose a scenario where government members are directly elected by the people, and seek to achieve proportional representation in the process. We will present a formal model for the allocation of K offices, each associated with a disjoint set of candidates contesting for that seat. A group of voters provides ballots for each of the offices. Since using simple majority voting for each office independently may result in minority preferences being completely ignored, here we adapt the greedy version of proportional approval voting (GreedyPAV) to our framework. In the article Electing the Executive Branch you can find an in-depth explanation of the model and a demonstration - through computer-based simulations - of how voting for all offices together using this rule overcomes this weakness and upholds the axiom of proportionality. In this article, we will present the implementation of the algorithm (GreedyPAV) proposed by Rutvik Page, Ehud Shapiro, and Nimrod Talmon in the article mentioned above. In addition, we tested our implementation through a survey, the results of which will be presented and analyzed later in the article.

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。

↑