Social Choice in a Social Context: A Multivariate Algorithmics Perspective

社会背景下的社会选择：多元算法视角

• 批准号: 317459980
• 负责人: Professor Dr. Robert Bredereck
• 金额: --
• 依托单位: Department of Computer Science
• 依托单位国家: 德国
• 项目类别: Research Fellowships
• 财政年份: 2016
• 资助国家: 德国
• 起止时间: 2015-12-31 至 2016-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/317459980?language=en
• 关键词: Social; Choice; Context; Multivariate; Algorithmics

The goal of this research project is to revise and extend established models of Computational Social Choice in order to capture effects induced by the social neighborhood of the agents (e.g. voters in an election). Such effects may be of cooperative flavor (e.g. agents may cooperate if they know each other), of competitive flavor (e.g. agents behave strategically and anticipate their opponents to also behave strategically), or based on privacy issues (e.g. agents prefer not to reveal their complete preferences). I propose to analyze the influence of such effects on the algorithmic complexity. To this end, concepts from algorithmic game theory, multivariate algorithmics, social networks, and voting theory will be used. For the identification of tractable cases, restricted domains of preferences will play a decisive role.

本研究项目的目标是修改和扩展计算社会选择的既定模型，以捕捉由代理人的社会邻居（例如选举中的选民）引起的影响。这种影响可能是合作的（例如，如果代理人相互了解，他们可能会合作），竞争的（例如，代理人采取战略行动，并预期他们的对手也采取战略行动），或者基于隐私问题（例如，代理人不愿意透露他们的完整偏好）。我建议分析这些效应对算法复杂度的影响。为此，将使用算法博弈论、多元算法、社会网络和投票理论的概念。为了确定可处理的病例，受限制的偏好领域将发挥决定性作用。