Maximizing Utilitarian and Egalitarian Welfare of Fractional Hedonic Games on Tree-Like Graphs

Tesshu Hanaka, Airi Ikeyama, Hirotaka Ono

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Fractional hedonic games are coalition formation games where the utility of a player is determined by the average value they assign to the members of their coalition. These games are a variation of graph hedonic games, which are a class of coalition formation games that can be succinctly represented. Due to their applicability in network clustering and their relationship to graph hedonic games, fractional hedonic games have been extensively studied from various perspectives. However, finding welfare-maximizing partitions in fractional hedonic games is a challenging task due to the nonlinearity of utilities. In fact, it has been proven to be NP-hard in general and can be solved in polynomial time only for a limited number of graph classes, such as trees. This paper presents (pseudo)polynomial-time algorithms to compute welfare-maximizing partitions in fractional hedonic games on tree-like graphs. We consider two types of social welfare measures: utilitarian and egalitarian. Tree-like graphs refer to graphs with bounded treewidth and block graphs. An NP-hardness result demonstrates that the pseudopolynomial-time solvability is the best possible under the assumption P ≠ NP.

Original languageEnglish
Title of host publicationCombinatorial Optimization and Applications - 16th International Conference, COCOA 2023, Proceedings
EditorsWeili Wu, Jianxiong Guo
PublisherSpringer Science and Business Media Deutschland GmbH
Pages392-405
Number of pages14
ISBN (Print)9783031496103
DOIs
Publication statusPublished - 2024
Event16th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2023 - Hawai, United States
Duration: Dec 15 2023Dec 17 2023

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14461 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th Annual International Conference on Combinatorial Optimization and Applications, COCOA 2023
Country/TerritoryUnited States
CityHawai
Period12/15/2312/17/23

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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