Query-Based Committee Selection

2026-03-31

AI Summary

This work addresses the challenge of applying traditional multi-winner voting rules in large-scale or attention-constrained settings, where eliciting complete preference rankings from voters is impractical. To overcome this limitation, the authors propose a structured-query framework for multi-winner elections that approximates an optimal committee by querying voters’ preferences over subsets of candidates within a limited budget. They formally define a cognitive cost function and axiomatic evaluation criteria, and introduce a query strategy based on recursively partitioning the candidate set. Experimental results demonstrate that this approach significantly outperforms alternative querying mechanisms across various election models and multi-winner rules—such as k-Borda—achieving high committee selection accuracy while substantially reducing the information acquisition cost.

Abstract

Purpose: Multiwinner voting rules typically require full knowledge of voter preferences, which becomes impractical in large-scale or attention-limited settings. This paper investigates how accurately a winning committee can be approximated when voter preferences are elicited using a limited budget of structured queries. Methods: We introduce a query-based framework for multiwinner elections in which voter preferences are elicited through refinement queries over subsets of candidates under a limited budget. We analyse several cost functions that model the cognitive effort needed to answer such queries, propose axiomatic properties for evaluating them, and experimentally evaluate simple query-based committee selection rules across multiple election models. Results: Experimental results show that strategies based on recursively splitting candidate sets provide the best trade-off between elicitation cost and committee accuracy. Across several statistical models, these strategies approximate the outcome of k-Borda elections significantly more efficiently than alternative query types. Conclusion: The results demonstrate that well-designed query strategies can substantially reduce the amount of preference information required while still producing high-quality committee outcomes, suggesting that query-based elicitation is a promising approach for scalable multiwinner decision-making.

Problem

• multiwinner voting
• preference elicitation
• query-based selection
• limited budget
• committee selection

Innovation

• query-based elicitation
• multiwinner voting
• preference elicitation
• recursive splitting
• k-Borda approximation