Pragmatics of Multiwinner Voting: Algorithms and Preference Data Analysis

This proposal is in the area of computational social choice, an area on the intersection of computer science and economics. We study multiwinner elections, with a focus on a pragmatic approach.

Our goal is to provide a principled framework for applying multiwinner voting in various settings that may appear in real-life (ranging from small-scale elections in various institutions, through participatory budgeting settings, to applications directly within computer science).

In particular, we are interested in: (a) designing new, fast algorithms for computing the outcomes of multiwinner voting rules (results of such rules are often NP-hard to compute), also for new languages of specifying preferences that are needed in practical settings; (b) obtaining algorithmic and mathematical understanding of preference data; and (c) providing algorithms for analyzing elections and their results.

We are interested both in theoretical studies (designing new algorithms, analyzing computational complexity of election-related problems, establishing axiomatic features of multiwinner voting rules, etc.) and in experimental evaluations (finding out running times of algorithms, establishing their approximation ratios, evaluating properties of preference data, etc.).