论文标题
递延接受算法的同谋操纵
Accomplice Manipulation of the Deferred Acceptance Algorithm
论文作者
论文摘要
递延的接受算法是对稳定匹配问题的优雅解决方案,可确保市场上一侧的最佳性和真实性。尽管有这些理想的保证,但它很容易受到另一端代理商对偏好的战略性错误报告。我们研究了延期接受算法下的战略行为的新型模型:通过同伙操纵。在这里,拟议的一方的代理商(例如,一个女人)与提议方面的代理人合作(同伙)代表她操纵(可能是为了使他的比赛恶化)。我们表明,同伙的最佳操纵策略包括在他的真实列表中精确地促进一个女人(即不起眼的操纵)。该结构结果立即给出了用于计算最佳同伙操作的多项式时间算法。我们还研究了操纵匹配相对于真实偏好稳定的条件。我们的实验结果表明,在发生频率和匹配伙伴的质量方面,Chare Ranigulation的表现都优于自我操纵。
The deferred acceptance algorithm is an elegant solution to the stable matching problem that guarantees optimality and truthfulness for one side of the market. Despite these desirable guarantees, it is susceptible to strategic misreporting of preferences by the agents on the other side. We study a novel model of strategic behavior under the deferred acceptance algorithm: manipulation through an accomplice. Here, an agent on the proposed-to side (say, a woman) partners with an agent on the proposing side -- an accomplice -- to manipulate on her behalf (possibly at the expense of worsening his match). We show that the optimal manipulation strategy for an accomplice comprises of promoting exactly one woman in his true list (i.e., an inconspicuous manipulation). This structural result immediately gives a polynomial-time algorithm for computing an optimal accomplice manipulation. We also study the conditions under which the manipulated matching is stable with respect to the true preferences. Our experimental results show that accomplice manipulation outperforms self manipulation both in terms of the frequency of occurrence as well as the quality of matched partners.