Ganian, R., Hamm, T., Knop, D. et al. (3 more authors) (2023) Maximizing Social Welfare in Score-Based Social Distance Games. Electronic Proceedings in Theoretical Computer Science, 379. pp. 272-286. ISSN 2075-2180
Abstract
Social distance games have been extensively studied as a coalition formation model where the utilities of agents in each coalition were captured using a utility function u that took into account distances in a given social network. In this paper, we consider a non-normalized score-based definition of social distance games where the utility function us̃ depends on a generic scoring vectors̃, which may be customized to match the specifics of each individual application scenario. As our main technical contribution, we establish the tractability of computing a welfare-maximizing partitioning of the agents into coalitions on tree-like networks, for every score-based function us̃. We provide more efficient algorithms when dealing with specific choices of us̃ or simpler networks, and also extend all of these results to computing coalitions that are Nash stable or individually rational. We view these results as a further strong indication of the usefulness of the proposed score-based utility function: even on very simple networks, the problem of computing a welfare-maximizing partitioning into coalitions remains open for the originally considered canonical function u.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © R. Ganian, T. Hamm, D. Knop, S. Roy, S. Schierreich & O. Such´y ˇ This work is licensed under the Creative Commons Attribution License. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 14 Feb 2024 08:55 |
Last Modified: | 15 Feb 2024 11:25 |
Status: | Published |
Publisher: | Open Publishing Association |
Identification Number: | 10.4204/eptcs.379.22 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:209175 |