More Efforts Towards Fixed-Parameter Approximability of Multiwinner Rules

More Efforts Towards Fixed-Parameter Approximability of Multiwinner Rules

Sushmita Gupta, Pallavi Jain, Souvik Saha, Saket Saurabh, Anannya Upasana

Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence
Main Track. Pages 3891-3899. https://doi.org/10.24963/ijcai.2025/433

Multiwinner Elections have emerged as a prominent area of research with numerous practical applications. Given a set of candidates, C, a set of voters, V, approving a subset of candidates (called approval set of a voter), and an integer k, we consider the problem of selecting a ``good'' committee using Thiele rules. This problem is computationally challenging for most Thiele rules with monotone submodular satisfaction functions, as there is no (1-1/e- epsilon) approximation algorithm in f(k)(|C| + |V|)^(o(k)) time for any fixed epsilon > 0 and any computable function f, and no PTAS even when the length of approval set is two. Skowron designed an approximation scheme running in FPT time parameterized by the combined parameter, size of the approval set, and k. In this paper, we consider a parameter d+k (no d voters approve the same set of d candidates), where d is upper bounded by the size of the approval set (thus, can be much smaller). With respect to this parameter, we design parameterized approximation schemes, a lossy polynomial-time preprocessing method, and show that an extra committee member suffices to achieve the desired score (i.e., 1-additive approximation). Additionally, we resolve an open question by Yang and Wang regarding the fixed-parameter tractability of the problem under the PAV rule with the total score as the parameter, demonstrating that it admits an FPT algorithm.
Keywords:
Game Theory and Economic Paradigms: GTEP: Computational social choice