Partition Aggregation for Participatory Budgeting

Pallavi Jain, Nimrod Talmon, Laurent Bulteau

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

3 Scopus citations


Recently, Jain et al. [IJCAI, 2019] studied the effect of project interactions in participatory budgeting (PB) by assuming an existing partition of the projects to interaction structures, namely a grouping of the projects into substitution and complementarity groups. Motivated by their study, here we take voter preferences to find such interaction structures. In our model, voters submit interaction structures, and the goal is to find an aggregated structure. Formally, given a set P of m projects, and n partitions of P, the task is to aggregate these n partitions into one aggregated partition. We consider this partition aggregation task both for substitution structures and for complementarity structures, studying several aggregation methods for each, including utility-based methods and Condorcet-based methods; we evaluate these methods by analyzing their computational complexity and their behavior with respect to certain relevant axiomatic properties.

Original languageEnglish
Title of host publicationProceedings of the 20th International Conference on Autonomous Agents and MultiAgent Systems
PublisherInternational Foundation for Autonomous Agents and Multiagent Systems (IFAAMAS)
Number of pages9
ISBN (Electronic)9781713832621
StatePublished - May 2021
Event20th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2021 - Virtual, Online
Duration: 3 May 20217 May 2021

Publication series

NameProceedings of the International Joint Conference on Autonomous Agents and Multiagent Systems, AAMAS
ISSN (Print)1548-8403
ISSN (Electronic)1558-2914


Conference20th International Conference on Autonomous Agents and Multiagent Systems, AAMAS 2021
CityVirtual, Online


  • Axiomatic analysis
  • Computational complexity
  • Participatory budgeting
  • Project interactions

ASJC Scopus subject areas

  • Artificial Intelligence
  • Software
  • Control and Systems Engineering


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