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Lie on the Fly: Strategic Voting in an Iterative Preference Elicitation Process

机译:即时说谎:迭代偏好启发过程中的战略投票

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摘要

A voting center is in charge of collecting and aggregating voter preferences. In an iterative process, the center sends comparison queries to voters, requesting them to submit their preference between two items. Voters might discuss the candidates among themselves, figuring out during the elicitation process which candidates stand a chance of winning and which do not. Consequently, strategic voters might attempt to manipulate by deviating from their true preferences and instead submit a different response in order to attempt to maximize their profit. We provide a practical algorithm for strategic voters which computes the best manipulative vote and maximizes the voter's selfish outcome when such a vote exists. We also provide a careful voting center which is aware of the possible manipulations and avoids manipulative queries when possible. In an empirical study on four real world domains, we show that in practice manipulation occurs in a low percentage of settings and has a low impact on the final outcome. The careful voting center reduces manipulation even further, thus allowing for a non-distorted group decision process to take place.We thus provide a core technology study of a voting process that can be adopted in opinion or information aggregation systems and in crowdsourcing applications, e.g., peer grading in massive open online courses.
机译:投票中心负责收集和汇总选民的喜好。在一个迭代过程中,中心将比较查询发送给选民,要求他们在两个项目之间提交自己的偏好。选民可能会在候选人之间讨论候选人,从而在启发过程中找出哪些候选人有获胜的机会,哪些没有机会。因此,战略选民可能会试图通过偏离自己的真实偏好而进行操纵,而是提出不同的回应,以试图最大限度地提高其利润。我们为战略选民提供了一种实用的算法,该算法可以计算出最佳的操纵性选票,并在存在这种选票时最大化选民的自私结果。我们还提供了一个仔细的投票中心,该投票中心了解可能的操纵方式,并在可能的情况下避免进行操纵性查询。在对四个现实世界域的实证研究中,我们表明,实际上,操纵发生在设置的百分比较低的地方,并且对最终结果的影响也很小。谨慎的投票中心甚至进一步减少了操纵,从而允许进行不失真的群体决策过程。因此,我们提供了对投票过程的核心技术研究,可以在意见或信息汇总系统以及众包应用(例如众包应用)中采用,在大规模的在线公开课程中进行同伴评分。

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