TY - GEN
T1 - Participatory Budgeting with Project Groups
AU - Jain, Pallavi
AU - Sornat, Krzysztof
AU - Talmon, Nimrod
AU - Zehavi, Meirav
N1 - Funding Information:
K. Sornat was partially supported by the Foundation for Polish Science (FNP) within the START programme, the National Science Centre, Poland (NCN; Grant No. 2018/28/T/ST6/00366) and the Israel Science Foundation (ISF; Grant No. 630/19). N. Talmon was supported by the Israel Science Foundation (ISF; Grant No. 630/19). M. Zehavi was supported by the Israel Science Foundation (ISF; Grant No. 1176/18) and the United States-Israel Binational Science Foundation (BSF; Grant No. 2018302). This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (ERC; Grant No. 101002854).
Funding Information:
K. Sornat was partially supported by the Foundation for Polish Science (FNP) within the START programme, the National Science Centre, Poland (NCN; Grant No. 2018/28/T/ST6/00366) and the Israel Science Foundation (ISF; Grant No. 630/19). N. Talmon was supported by the Israel Science Foundation (ISF; Grant No. 630/19). M. Zehavi was supported by the Israel Science Foundation (ISF; Grant No. 1176/18) and the United States-Israel Binational Science Foundation (BSF; Grant No. 2018302). This project has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (ERC; Grant No. 101002854).
Publisher Copyright:
© 2021 International Joint Conferences on Artificial Intelligence. All rights reserved.
PY - 2021/1/1
Y1 - 2021/1/1
N2 - We study a generalization of the standard approval-based model of participatory budgeting (PB), in which voters are providing approval ballots over a set of predefined projects and-in addition to a global budget limit-there are several groupings of the projects, each group with its own budget limit. We study the computational complexity of identifying project bundles that maximize voter satisfaction while respecting all budget limits. We show that the problem is generally intractable and describe efficient exact algorithms for several special cases, including instances with only few groups and instances where the group structure is close to being hierarchical, as well as efficient approximation algorithms. Our results could allow, e.g., municipalities to hold richer PB processes that are thematically and geographically inclusive.
AB - We study a generalization of the standard approval-based model of participatory budgeting (PB), in which voters are providing approval ballots over a set of predefined projects and-in addition to a global budget limit-there are several groupings of the projects, each group with its own budget limit. We study the computational complexity of identifying project bundles that maximize voter satisfaction while respecting all budget limits. We show that the problem is generally intractable and describe efficient exact algorithms for several special cases, including instances with only few groups and instances where the group structure is close to being hierarchical, as well as efficient approximation algorithms. Our results could allow, e.g., municipalities to hold richer PB processes that are thematically and geographically inclusive.
UR - http://www.scopus.com/inward/record.url?scp=85125463728&partnerID=8YFLogxK
M3 - Conference contribution
T3 - IJCAI International Joint Conference on Artificial Intelligence
SP - 276
EP - 282
BT - Proceedings of the 30th International Joint Conference on Artificial Intelligence, IJCAI 2021
A2 - Zhou, Zhi-Hua
PB - International Joint Conferences on Artificial Intelligence
T2 - 30th International Joint Conference on Artificial Intelligence, IJCAI 2021
Y2 - 19 August 2021 through 27 August 2021
ER -
