Abstract
A general framework for approval-based participatory budgeting has recently been introduced by Talmon and Faliszewski [17]. They use satisfaction functions to model the voters’ agreement with a given outcome based on their approval ballots. We adopt two of their satisfaction functions and focus on two types of rules. That is, rules that maximize the overall voters’ satisfaction and greedy rules that iteratively extend a partial budget by an item that maximizes the satisfaction in each incremental step. An important task in participatory budgeting is to study different forms of manipulative interference that may occur in practice. We investigate the computational complexity of different problems related to determining the outcome of a given rule and give a very general formulation of manipulative interference problems. A special focus is on problems dealing with a varying cost of the items and a varying budget limit. The results range from polynomial-time algorithms to completeness in different levels of the polynomial hierarchy.
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Acknowledgment
We thank all reviewers for their helpful comments. Supported in part by DFG grant BA 6270/1-1 and by the project “Online Participation,” funded by the NRW Ministry for Innovation, Science, and Research.
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Baumeister, D., Boes, L., Hillebrand, J. (2021). Complexity of Manipulative Interference in Participatory Budgeting. In: Fotakis, D., Ríos Insua, D. (eds) Algorithmic Decision Theory. ADT 2021. Lecture Notes in Computer Science(), vol 13023. Springer, Cham. https://doi.org/10.1007/978-3-030-87756-9_27
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DOI: https://doi.org/10.1007/978-3-030-87756-9_27
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