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Talks and Poster Presentations (with Proceedings-Entry):

E. Eiben, R. Ganian, T. Hamm, S. Ordyniak:
"Parameterized Complexity of Envy-Free Resource Allocation in Social Networks";
Talk: 34th AAAI Conference on Artificial Intelligence (AAAI-20), New York, New York, USA; 2020-02-07 - 2020-02-12; in: "The Thirty-Fourth AAAI Conference on Artificial Intelligence", AAAI Press, 34 (2020), ISSN: 2159-5399; 7135 - 7142.



English abstract:
We consider the classical problem of allocating 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 items. In particular, we show that even very general fragments of the considered problems become tractable as long as the social network has bounded treewidth or bounded clique-width. We complement our results with matching lower bounds which show that our algorithms cannot be substantially improved.


"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
http://dx.doi.org/10.1609/aaai.v34i05.6201

Electronic version of the publication:
https://publik.tuwien.ac.at/files/publik_293756.pdf


Created from the Publication Database of the Vienna University of Technology.