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Main Authors: Han, Qishen, Ivaniuk, Artem, Elkind, Edith, Xia, Lirong
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2601.17538
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author Han, Qishen
Ivaniuk, Artem
Elkind, Edith
Xia, Lirong
author_facet Han, Qishen
Ivaniuk, Artem
Elkind, Edith
Xia, Lirong
contents Participatory Budgeting (PB) is commonly studied from an axiomatic perspective, where the aim is to design procedurally fair and economically efficient rules for voters with full information regarding their preferences. In contrast, we take an epistemic perspective and consider a framework where PB projects have different levels of underlying quality, indicating how well the project will take effect, which cannot be directly observed before implementation. Agents with noisy information cast votes to aggregate their information, and aim to elect a high-quality set of projects. We evaluate the performance of common PB rules by measuring the expected utility of their outcomes, compared to the optimal set of projects. We find that the quality of approximation improves as the range of project costs shrinks. When projects have unit cost, these common rules can identify the ``best'' set with probability converging to 1. We also study whether strategic agents have incentives to honestly convey their information in the vote. We find that it happens only under very restrictive conditions. We also run numerical experiments to examine the performance of different rules empirically and support our theoretical findings.
format Preprint
id arxiv_https___arxiv_org_abs_2601_17538
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Truth-Revealing Participatory Budgeting
Han, Qishen
Ivaniuk, Artem
Elkind, Edith
Xia, Lirong
Computer Science and Game Theory
Participatory Budgeting (PB) is commonly studied from an axiomatic perspective, where the aim is to design procedurally fair and economically efficient rules for voters with full information regarding their preferences. In contrast, we take an epistemic perspective and consider a framework where PB projects have different levels of underlying quality, indicating how well the project will take effect, which cannot be directly observed before implementation. Agents with noisy information cast votes to aggregate their information, and aim to elect a high-quality set of projects. We evaluate the performance of common PB rules by measuring the expected utility of their outcomes, compared to the optimal set of projects. We find that the quality of approximation improves as the range of project costs shrinks. When projects have unit cost, these common rules can identify the ``best'' set with probability converging to 1. We also study whether strategic agents have incentives to honestly convey their information in the vote. We find that it happens only under very restrictive conditions. We also run numerical experiments to examine the performance of different rules empirically and support our theoretical findings.
title Truth-Revealing Participatory Budgeting
topic Computer Science and Game Theory
url https://arxiv.org/abs/2601.17538