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Discrete Budget Aggregation: Truthfulness and Proportionality

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Abstract

We study a budget aggregation setting where voters express their preferred allocation of a fixed budget over a set of alternatives, and a mechanism aggregates these preferences into a single output allocation. Motivated by scenarios in which the budget is not perfectly divisible, we depart from the prevailing literature by restricting the mechanism to output allocations that assign integral amounts. This seemingly minor deviation has significant implications for the existence of truthful mechanisms. Specifically, when voters can propose fractional allocations, we demonstrate that the Gibbard-Satterthwaite theorem can be extended to our setting. In contrast, when voters are restricted to integral ballots, we identify a class of truthful mechanisms by adapting moving-phantom mechanisms to our context. Finally, we show that while a weak form of proportionality can be achieved alongside truthfulness, stronger proportionality notions derived from approval-based committee voting are incompatible with truthfulness.
Original languageEnglish
Title of host publicationProceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence (IJCAI-25)
EditorsJames Kwok
PublisherInternational Joint Conferences on Artificial Intelligence (IJCAI)
Pages4040-4047
Number of pages8
ISBN (Electronic)978-1-956792-06-5
DOIs
Publication statusPublished - Aug 2025
Event34th International Joint Conference on Artificial Intelligence, IJCAI 2025 - Montreal, Canada
Duration: 16 Aug 202522 Aug 2025
Conference number: 34

Conference

Conference34th International Joint Conference on Artificial Intelligence, IJCAI 2025
Abbreviated titleIJCAI 2025
Country/TerritoryCanada
CityMontreal
Period16/08/2522/08/25

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