TY - GEN
T1 - Submodular Participatory Budgeting
AU - Yuan, Jing
AU - Tang, Shaojie
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
PY - 2024
Y1 - 2024
N2 - 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.
AB - 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.
KW - Distortion
KW - Participatory Budgeting
KW - Submodular Optimization
UR - https://www.scopus.com/pages/publications/85205394538
U2 - 10.1007/978-981-97-7798-3_19
DO - 10.1007/978-981-97-7798-3_19
M3 - Conference contribution
AN - SCOPUS:85205394538
SN - 9789819777976
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 222
EP - 234
BT - Algorithmic Aspects in Information and Management - 18th International Conference, AAIM 2024, Proceedings
A2 - Ghosh, Smita
A2 - Zhang, Zhao
PB - Springer Science and Business Media Deutschland GmbH
T2 - 18th International Conference on Algorithmic Aspects in Information and Management, AAIM 2024
Y2 - 21 September 2024 through 23 September 2024
ER -