<div class="csl-bib-body">
<div class="csl-entry">Eiben, E., Ganian, R., Hamm, T., & Ordyniak, S. (2023). Parameterized complexity of envy-free resource allocation in social networks. <i>Artificial Intelligence</i>, <i>315</i>, Article 103826. https://doi.org/10.1016/j.artint.2022.103826</div>
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dc.identifier.issn
0004-3702
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dc.identifier.uri
http://hdl.handle.net/20.500.12708/188030
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dc.description.abstract
We consider the classical problem of allocating indivisible resources among agents in an envy-free (and, where applicable, proportional) way. Recently, the basic model was enriched by introducing the concept of a social network which allows to capture situations where agents might not have full information about the allocation of all resources. We initiate the study of the parameterized complexity of these resource allocation problems by considering natural parameters which capture structural properties of the network and similarities between agents and resources. In particular, we show that even very general fragments of the considered problems become tractable as long as the social network has constant treewidth or clique-width. We complement our results with matching lower bounds which show that our algorithms cannot be substantially improved.
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dc.language.iso
en
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dc.publisher
ELSEVIER
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dc.relation.ispartof
Artificial Intelligence
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dc.subject
Clique-width
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dc.subject
Computational social choice
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dc.subject
Parameterized complexity
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dc.subject
Resource allocation
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dc.subject
Treewidth
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dc.title
Parameterized complexity of envy-free resource allocation in social networks