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Submodular Participatory Budgeting

  • University of North Texas

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Participatory budgeting refers to the practice of allocating public resources by collecting and aggregating individual preferences. Most existing studies in this field often assume an additive utility function, where each individual holds a private utility for each candidate project, and the total utility of a set of funded projects is simply the sum of the utilities of all projects. We argue that this assumption does not always hold in reality. For example, building two playgrounds in the same neighborhood does not necessarily lead to twice the utility of building a single playground. To address this, we extend the existing study by proposing a submodular participatory budgeting problem, assuming that the utility function of each individual is a monotone and submodular function over funded projects. We propose and examine three preference elicitation methods and analyze their performances in terms of distortion. Notably, if the utility function is additive, our aggregation rule designed for threshold approval votes achieves a better distortion than the state-of-the-art approach.

Original languageEnglish
Title of host publicationAlgorithmic Aspects in Information and Management - 18th International Conference, AAIM 2024, Proceedings
EditorsSmita Ghosh, Zhao Zhang
PublisherSpringer Science and Business Media Deutschland GmbH
Pages222-234
Number of pages13
ISBN (Print)9789819777976
DOIs
StatePublished - 2024
Event18th International Conference on Algorithmic Aspects in Information and Management, AAIM 2024 - Virtual, Online
Duration: Sep 21 2024Sep 23 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume15179 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Algorithmic Aspects in Information and Management, AAIM 2024
CityVirtual, Online
Period09/21/2409/23/24

Keywords

  • Distortion
  • Participatory Budgeting
  • Submodular Optimization

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