Social Choice in a Social Context: A Multivariate Algorithmics Perspective

本研究项目的目标是修正和扩展已建立的计算社会选择模型，以捕捉代理人(例如选举中的选民)的社会邻里关系所引起的影响。这种影响可能是合作的(例如，代理可以在彼此认识的情况下进行合作)，也可能是竞争的(例如，代理的行为是战略性的，并预计对手也会战略性地行为)，或者基于隐私问题(例如，代理不愿透露他们的完全偏好)。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、多变量算法、社会网络和投票理论的概念。在确定可处理案件方面，受限制的优惠领域将发挥决定性作用。

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.