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引用次数: 0
摘要
摘要 大学某系的 n 位专家组成的委员会必须从 m 位候选人中选择聘用人选。他们对最佳候选人的真实判断必须汇总起来,以确定社会最优候选人。然而,专家的判断是无法验证的。此外,每位专家的判断并不一定决定他对候选人的偏好。为了解决这个问题,必须设计一种机制来实现社会最优的汇总规则。我们证明,与q-supermajoritarian和纳什可实施的聚合规则相容的最小配额q是(q=n-\leftlfloor \frac{n-1}{m}\right\rfloor\) 。此外,要使这样的规则存在,就每对候选人而言,必须至少有(m\left\lfloor \frac{n-1}{m}\right\rfloor +1\ )个公正的专家。
A committee of n experts from a university department must choose whom to hire from a set of m candidates. Their honest judgments about the best candidate must be aggregated to determine the socially optimal candidates. However, experts’ judgments are not verifiable. Furthermore, the judgment of each expert does not necessarily determine his preferences over candidates. To solve this problem, a mechanism that implements the socially optimal aggregation rule must be designed. We show that the smallest quota q compatible with the existence of a q-supermajoritarian and Nash implementable aggregation rule is \(q=n-\left\lfloor \frac{n-1}{m}\right\rfloor\). Moreover, for such a rule to exist, there must be at least \(m\left\lfloor \frac{n-1}{m}\right\rfloor +1\) impartial experts with respect to each pair of candidates.
期刊介绍:
International Journal of Game Theory is devoted to game theory and its applications. It publishes original research making significant contributions from a methodological, conceptual or mathematical point of view. Survey articles may also be considered if especially useful for the field.