Parameterized Algorithmics for Computational Social Choice: Nine Research Challenges

TL;DR

This paper outlines nine key research challenges in applying parameterized algorithmics to computational social choice, aiming to identify tractable cases of complex problems in voting and preference aggregation.

Contribution

It introduces nine research challenges that explore the parameterized complexity of problems in computational social choice, bridging theory and practical applications.

Findings

Identification of nine key research challenges

Highlighting the potential of parameterized complexity in social choice

Guiding future research directions in the field

Abstract

Computational Social Choice is an interdisciplinary research area involving Economics, Political Science, and Social Science on the one side, and Mathematics and Computer Science (including Artificial Intelligence and Multiagent Systems) on the other side. Typical computational problems studied in this field include the vulnerability of voting procedures against attacks, or preference aggregation in multi-agent systems. Parameterized Algorithmics is a subfield of Theoretical Computer Science seeking to exploit meaningful problem-specific parameters in order to identify tractable special cases of in general computationally hard problems. In this paper, we propose nine of our favorite research challenges concerning the parameterized complexity of problems appearing in this context.