<div class="csl-bib-body">
<div class="csl-entry">Lackner, M., Regner, P., & Krenn, B. (2023). abcvoting: A Python package for approval-based multi-winner voting rules. <i>Journal of Open Source Software</i>, <i>8</i>(81), 1–3. https://doi.org/10.21105/joss.04880</div>
</div>
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/204473
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dc.description.abstract
The Python package abcvoting is a research tool to explore and analyse approval-based committee (ABC) elections. First and
foremost, it contains implementations of major ABC voting rules. These are voting rules that accept as input approval ballots, that is, the (binary) preferences of voters expressing which candidates they like or support. The output is a fixed-size subset of candidates, called a committee. Different ABC voting rules represent different approaches how such a committee should be formed. For example, there is a trade-off between selecting only widely supported candidates and choosing a committee that represent as many voters as possible. Much of the recent research has focussed on developing ABC voting rules that reflect the preferences of voters in a proportional fashion.
abcvoting is primarily intended for researchers interested in voting and related algorithmic challenges. The core content of abcvoting are implementations of a large number of ABC voting rules. These allow a user to quickly compute (and compare) winning committees for all implemented voting rules. In addition to computing winning committees, abcvoting can be used to verify axiomatic properties of committees. Axiomatic properties are mathematical formalizations of desirable features, e.g, fairness guarantees. Such properties are fundamental to the analysis and discussion of voting rules.
en
dc.description.sponsorship
FWF - Österr. Wissenschaftsfonds
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dc.language.iso
en
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dc.publisher
Journal of Open Source Software
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dc.relation.ispartof
Journal of Open Source Software
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dc.rights.uri
http://creativecommons.org/licenses/by/4.0/
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dc.subject
computational social choice
en
dc.subject
multi-winner voting
en
dc.subject
Python package
en
dc.subject
integer linear programming
en
dc.subject
optimization
en
dc.title
abcvoting: A Python package for approval-based multi-winner voting rules
en
dc.type
Article
en
dc.type
Artikel
de
dc.rights.license
Creative Commons Namensnennung 4.0 International
de
dc.rights.license
Creative Commons Attribution 4.0 International
en
dc.contributor.affiliation
TU Wien
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dc.description.startpage
1
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dc.description.endpage
3
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dc.relation.grantno
P 31890-N31
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dc.rights.holder
Authors of papers retain copyright
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dc.type.category
Original Research Article
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tuw.container.volume
8
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tuw.container.issue
81
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tuw.journal.peerreviewed
true
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tuw.peerreviewed
true
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tuw.project.title
Algorithms for Sustainable Group Decision Making
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tuw.researchTopic.id
C4
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tuw.researchTopic.name
Mathematical and Algorithmic Foundations
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tuw.researchTopic.value
100
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dcterms.isPartOf.title
Journal of Open Source Software
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tuw.publication.orgunit
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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tuw.publisher.doi
10.21105/joss.04880
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dc.identifier.eissn
2475-9066
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dc.identifier.libraryid
AC17364287
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dc.description.numberOfPages
3
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tuw.author.orcid
0000-0003-2170-0770
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tuw.author.orcid
0000-0001-8480-4900
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dc.rights.identifier
CC BY 4.0
de
dc.rights.identifier
CC BY 4.0
en
wb.sciencebranch
Informatik
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wb.sciencebranch.oefos
1020
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wb.sciencebranch.value
100
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Publications
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with Fulltext
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application/pdf
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item.languageiso639-1
en
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item.openairetype
research article
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item.openaccessfulltext
Open Access
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http://purl.org/coar/resource_type/c_2df8fbb1
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item.grantfulltext
open
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crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence
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crisitem.author.dept
TU Wien
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crisitem.author.dept
E192-02 - Forschungsbereich Databases and Artificial Intelligence