HCC: Computational Social Choice

这个项目将扩大和推进投票系统的理解，认为这些系统是聚集代理人的偏好，以选择一组赢家的方法开始。该项目将通过提取选举复杂性的来源来对投票系统进行分类。理想情况下，通过二分法的结果完全表征哪些系统是复杂的，哪些是容易的，对于关键的选举问题，如控制，贿赂和操纵。该项目将扩大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地扩展到不完全信息模型中。这项工作与社会选择、经济学、政治学、数学和运筹学中感兴趣的问题密切相关。选举被人类和（电子）多代理系统广泛使用，因此保护这些系统免受操纵对计算机科学和社会都具有极其重要的意义。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难以完成任务。

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.