Approximate Strategyproofness in Approval-Based Budget Division

Approximate Strategyproofness in Approval-Based Budget Division

Haris Aziz, Patrick Lederer, Jeremy Vollen

Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence
Main Track. Pages 3341-3349. https://doi.org/10.24963/ijcai.2026/371

In approval-based budget division, the task is to allocate a divisible resource to the candidates based on the voters' approval preferences over the candidates. For this setting, Brandl et al. (2021) have shown that no distribution rule can be strategyproof, efficient, and fair at the same time. In this paper, we aim to circumvent this impossibility theorem by focusing on approximate strategyproofness. To this end, we analyze the incentive ratio of distribution rules, which quantifies the maximum multiplicative utility gain of a voter by manipulating. While it turns out that several classical rules have a large incentive ratio, we prove that the Nash product rule (NASH) has an incentive ratio of 2, thereby demonstrating that we can bypass the impossibility of Brandl et al. by relaxing strategyproofness. Moreover, we show that an incentive ratio of 2 is optimal within three natural classes of rules and that the positive result for the Nash product rule even holds when voters may report arbitrary concave utility functions. Finally, we complement our results with an experimental analysis.
Keywords:
Game Theory and Economic Paradigms: Computational social choice
Game Theory and Economic Paradigms: Mechanism design