<div class="csl-bib-body">
<div class="csl-entry">Chen, J., Lackner, M., & Maly, J. (2022). Participatory Budgeting with Donations and Diversity Constraints. In <i>Proceedings of the AAAI Conference on Artificial Intelligence</i> (pp. 9323–9330). AAAI Press. https://doi.org/10.1609/aaai.v36i9.21163</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/144351
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dc.description.abstract
Participatory budgeting (PB) is a democratic process where citizens jointly decide on how to allocate public funds to indivisible projects. In this work, we focus on PB processes where citizens may provide additional money to projects they want to see funded. We introduce a formal framework for this kind of PB with donations. Our framework also allows for diversity constraints, meaning that each project belongs to one or more types, and there are lower and upper bounds on the number of projects of the same type that can be funded. We propose three general classes of methods for aggregating the citizens’ preferences in the presence of donations and analyze their axiomatic properties. Furthermore, we investigate the computational complexity of determining the outcome of a PB process with donations and of finding a citizen’s optimal donation strategy.
en
dc.description.sponsorship
Fonds zur Förderung der wissenschaftlichen Forschung (FWF)
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dc.language.iso
en
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dc.subject
Multiagent Systems (MAS)
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dc.subject
Participatory Budgeting
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dc.subject
Donations
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dc.subject
Diversity Constraints
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dc.subject
framework
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dc.subject
aggregating
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dc.subject
analyze
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dc.subject
axiomatic properties
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dc.subject
computational complexity
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dc.subject
determining
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dc.subject
Strategy
en
dc.title
Participatory Budgeting with Donations and Diversity Constraints
en
dc.type
Inproceedings
en
dc.type
Konferenzbeitrag
de
dc.relation.isbn
1-57735-876-7
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dc.description.startpage
9323
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dc.description.endpage
9330
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dc.relation.grantno
P31890-N31
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dc.type.category
Full-Paper Contribution
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tuw.booktitle
Proceedings of the AAAI Conference on Artificial Intelligence
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tuw.container.volume
36(9)
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tuw.peerreviewed
true
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tuw.relation.publisher
AAAI Press
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tuw.relation.publisherplace
Palo Alto, CA, USA
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tuw.project.title
Algorithms for Sustainable Group Decision Making
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tuw.researchTopic.id
I1
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tuw.researchTopic.name
Logic and Computation
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tuw.researchTopic.value
100
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tuw.publication.orgunit
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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tuw.publisher.doi
10.1609/aaai.v36i9.21163
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dc.description.numberOfPages
8
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tuw.author.orcid
0000-0003-2170-0770
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tuw.event.name
36th AAAI Conference on Artificial Intelligence (AAAI 2022)
en
dc.description.sponsorshipexternal
WWTF
-
dc.description.sponsorshipexternal
FWF
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dc.relation.grantnoexternal
VRG18-012
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dc.relation.grantnoexternal
J4581
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tuw.event.startdate
22-02-2022
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tuw.event.enddate
01-03-2022
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tuw.event.online
Online
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tuw.event.type
Event for scientific audience
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tuw.event.country
US
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tuw.event.presenter
Lackner, Martin
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tuw.presentation.online
Online
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wb.sciencebranch
Informatik
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wb.sciencebranch
Mathematik
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.oefos
1010
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wb.sciencebranch.value
80
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wb.sciencebranch.value
20
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item.languageiso639-1
en
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item.openairetype
conference paper
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item.grantfulltext
restricted
-
item.fulltext
no Fulltext
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item.cerifentitytype
Publications
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item.openairecristype
http://purl.org/coar/resource_type/c_5794
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crisitem.author.dept
E192-01 - Forschungsbereich Algorithms and Complexity
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crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence