摘要翻译：
利用非加权Borda规则研究了选举中的联盟操纵问题。我们以两种新的贪婪操作算法的形式提供了Borda选举可操作性的经验证据，这些算法基于装箱和多处理机调度领域的直觉。虽然我们还不能证明这些算法在最坏的情况下击败了现有的方法，但我们的经验评估表明，它们显著优于现有的方法，并且能够在我们测试的绝大多数随机产生的选举中找到最佳操纵。这些实证结果提供了进一步的证据，表明Borda规则对联盟操纵提供了很少的防御。
---
英文标题：
《An Empirical Study of Borda Manipulation》
---
作者：
Jessica Davies and George Katsirelos and Nina Narodystka and Toby
  Walsh
---
最新提交年份：
2010
---
分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
--

---
英文摘要：
  We study the problem of coalitional manipulation in elections using the unweighted Borda rule. We provide empirical evidence of the manipulability of Borda elections in the form of two new greedy manipulation algorithms based on intuitions from the bin-packing and multiprocessor scheduling domains. Although we have not been able to show that these algorithms beat existing methods in the worst-case, our empirical evaluation shows that they significantly outperform the existing method and are able to find optimal manipulations in the vast majority of the randomly generated elections that we tested. These empirical results provide further evidence that the Borda rule provides little defense against coalitional manipulation.
---
PDF链接：
https://arxiv.org/pdf/1007.5104