Approximate Strategyproofness in Approval-Based Budget Division
Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence. Main Track. Pages 3341-3349.
https://doi.org/10.24963/ijcai.2026/371
Keywords
- Game Theory and Economic Paradigms: Computational social choice
- Game Theory and Economic Paradigms: Mechanism design
Abstract
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.
@inproceedings{ijcai2026p371,
title = {Approximate Strategyproofness in Approval-Based Budget Division},
author = {Aziz, Haris and Lederer, Patrick and Vollen, Jeremy},
booktitle = {Proceedings of the Thirty-Fifth International Joint Conference on
Artificial Intelligence, {IJCAI-26}},
publisher = {International Joint Conferences on Artificial Intelligence Organization},
editor = {Diego Calvanese},
pages = {3341--3349},
year = {2026},
month = {8},
note = {Main Track},
doi = {10.24963/ijcai.2026/371},
url = {https://doi.org/10.24963/ijcai.2026/371},
}
TY - CPAPER TI - Approximate Strategyproofness in Approval-Based Budget Division AU - Aziz, Haris AU - Lederer, Patrick AU - Vollen, Jeremy T2 - Proceedings of the Thirty-Fifth International Joint Conference on Artificial Intelligence, IJCAI-26 PB - International Joint Conferences on Artificial Intelligence Organization PY - 2026 SP - 3341 EP - 3349 DO - 10.24963/ijcai.2026/371 UR - https://doi.org/10.24963/ijcai.2026/371 ER -Copied
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