HCC: Computational Social Choice

这个项目将扩大和促进对投票系统的理解，首先认为这些系统是聚集代理人偏好以选择一组获胜者的方法。该项目将通过提取选举中复杂的来源来对投票系统进行分类-理想情况下，通过二分法结果完全表征对于控制、获胜、贿赂和操纵等关键选举问题，哪些系统是复杂的，哪些系统是容易的。该项目将拓宽这类选举结果的模型范围，特别是将现有的多项式时间算法尽可能扩展为不完全信息模型。这项工作与社会选择、经济学、政治学、数学和运筹学等领域的兴趣问题密切相关。选举被人类和(电子)多智能体系统广泛使用，因此保护此类系统免受操纵对计算机科学和社会都具有令人信服的重要性。复杂控制机制的发展以积极的方式利用复杂性，即利用复杂性使潜在的选举操纵者和控制者的任务变得困难。

This project will broaden and advance the understanding of voting systems starting with the view that these systems are methods of aggregating agent preferences to select a set of winners. The project will classify voting systems by extracting the source of complexity in elections?ideally via dichotomy results completely characterizing which systems are complex, and which are easy, for the key electoral questions such as control, winnership, bribery, and manipulation. The project will broaden the range of models for election results of this sort, and in particular will extend existing polynomial-time algorithms as far as possible into incomplete information models.This work is closely allied with issues of interest in social choice, economics, political science, mathematics, and operations research. Elections are used extensively by humans and in (electronic) multi-agent systems, and so protecting such systems against manipulation is of compelling importance to both computer science and society. The development of complex control mechanisms uses complexity in a positive way, namely, using complexity to make difficult the task of would-be electoral manipulators and controllers.