秩最大等贡献：一个概率社会选择函数
Rank Maximal Equal Contribution: a Probabilistic Social Choice Function
摘要：
当通过投票聚集代理人的偏好时，两个理想的目标是激励代理人参与投票过程，然后确定帕累托有效的结果。我们认为参与是Brandl，Brandt和Hofbauer（2015）基于随机优势（SD）关系的形式化。我们制定了一个新的规则，称为RMEC（排名最大相等贡献），满足最强的参与概念，也是事后有效的。该规则是多项式时间可计算的，也满足许多其他期望的公平性。该规则提出了实现事后效率和非常强有力的参与的一般性办法。
英文摘要：
When aggregating preferences of agents via voting, two desirable goals are to incentivize agents to participate in the voting process and then identify outcomes that are Pareto efficient. We consider participation as formalized by Brandl, Brandt, and Hofbauer (2015) based on the stochastic dominance (SD) relation. We formulate a new rule called RMEC (Rank Maximal Equal Contribution) that satisfies the strongest notion of participation and is also ex post efficient. The rule is polynomial-time computable and also satisfies many other desirable fairness properties. The rule suggests a general approach to achieving ex post efficiency and very strong participation.
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