Parameterized Complexity of Hedonic Games with Enemy-Oriented Preferences

Fuente: arXiv
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Auteurs principaux: Durand, Martin, Erlacher, Laurin, Vistisen, Johanne Müller, Simola, Sofia
Format: Preprint
Publié: 2025
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author Durand, Martin
Erlacher, Laurin
Vistisen, Johanne Müller
Simola, Sofia
author_facet Durand, Martin
Erlacher, Laurin
Vistisen, Johanne Müller
Simola, Sofia
contents Hedonic games model settings in which a set of agents have to be partitioned into groups which we call coalitions. In the enemy aversion model, each agent has friends and enemies, and an agent prefers to be in a coalition with as few enemies as possible and, subject to that, as many friends as possible. A partition should be stable, i.e., no subset of agents prefer to be together rather than being in their assigned coalition under the partition. We look at two stability concepts: core stability and strict core stability. This yields several algorithmic problems: determining whether a (strictly) core stable partition exists, finding such a partition, and checking whether a given partition is (strictly) core stable. Several of these problems have been shown to be NP-complete, or even beyond NP. This motivates the study of parameterized complexity. We conduct a thorough computational study using several parameters: treewidth, number of friends, number of enemies, partition size, and coalition size. We give polynomial algorithms for restricted graph classes as well as FPT algorithms with respect to the number of friends an agent may have and the treewidth of the graph representing the friendship or enemy relations. We show W[1]-hardness or para-NP-hardness with respect to the other parameters. We conclude this paper with results in the setting in which agents can have neutral relations with each other, including hardness-results for very restricted cases.
format Preprint
id arxiv_https___arxiv_org_abs_2502_13703
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Parameterized Complexity of Hedonic Games with Enemy-Oriented Preferences
Durand, Martin
Erlacher, Laurin
Vistisen, Johanne Müller
Simola, Sofia
Computer Science and Game Theory
Multiagent Systems
Hedonic games model settings in which a set of agents have to be partitioned into groups which we call coalitions. In the enemy aversion model, each agent has friends and enemies, and an agent prefers to be in a coalition with as few enemies as possible and, subject to that, as many friends as possible. A partition should be stable, i.e., no subset of agents prefer to be together rather than being in their assigned coalition under the partition. We look at two stability concepts: core stability and strict core stability. This yields several algorithmic problems: determining whether a (strictly) core stable partition exists, finding such a partition, and checking whether a given partition is (strictly) core stable. Several of these problems have been shown to be NP-complete, or even beyond NP. This motivates the study of parameterized complexity. We conduct a thorough computational study using several parameters: treewidth, number of friends, number of enemies, partition size, and coalition size. We give polynomial algorithms for restricted graph classes as well as FPT algorithms with respect to the number of friends an agent may have and the treewidth of the graph representing the friendship or enemy relations. We show W[1]-hardness or para-NP-hardness with respect to the other parameters. We conclude this paper with results in the setting in which agents can have neutral relations with each other, including hardness-results for very restricted cases.
title Parameterized Complexity of Hedonic Games with Enemy-Oriented Preferences
topic Computer Science and Game Theory
Multiagent Systems
url https://arxiv.org/abs/2502.13703