research-article

Graphical House Allocation

Authors:

Vignesh ViswanathanAuthors Info & Claims

AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems

Pages 161 - 169

Published: 30 May 2023 Publication History

Abstract

The classical house allocation problem involves assigning n houses (or items) to n agents according to their preferences. A key criteria in such problems is satisfying some fairness constraints such as envy-freeness. We consider a generalization of this problem wherein the agents are placed along the vertices of a graph (corresponding to a social network), and each agent can only experience envy towards its neighbors. Our goal is to minimize the aggregate envy among the agents as a natural fairness objective, i.e., the sum of the envy value over all edges in a social graph.

When agents have identical and evenly-spaced valuations, our problem reduces to the well-studied problem of linear arrangements. For identical valuations with possibly uneven spacing, we show a number of deep and surprising ways in which our setting is a departure from this classical problem. More broadly, we contribute several structural and computational results for various classes of graphs, including NP-hardness results for disjoint unions of paths, cycles, stars, or cliques; we also obtain fixed-parameter tractable (and, in some cases, polynomial-time) algorithms for paths, cycles, stars, cliques, and their disjoint unions.

Additionally, a conceptual contribution of our work is the formulation of a structural property for disconnected graphs that we call separability which results in efficient parameterized algorithms for finding optimal allocations.

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Cited By

Hosseini HMcGregor ASengupta RVaish RViswanathan VDastani MSichman JAlechina NDignum V(2024)Tight Approximations for Graphical House AllocationProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3662936(825-833)Online publication date: 6-May-2024
https://dl.acm.org/doi/10.5555/3635637.3662936

Index Terms

Graphical House Allocation
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Multi-agent systems
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Algorithmic game theory and mechanism design

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Abstract
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cover image ACM Conferences

AAMAS '23: Proceedings of the 2023 International Conference on Autonomous Agents and Multiagent Systems

May 2023

3131 pages

ISBN:9781450394321

General Chairs:
Noa Agmon
Bar-Ilan University, Israel
,
Bo An
Nanyang Technological University, Singapore
,
Program Chairs:
Alessandro Ricci
University of Bologna, Italy
,
William Yeoh
Washington University in St. Louis, USA

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International Foundation for Autonomous Agents and Multiagent Systems

Richland, SC

Publication History

Published: 30 May 2023

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DST INSPIRE
NSF

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AAMAS '23

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SIGAI

AAMAS '23: International Conference on Autonomous Agents and Multiagent Systems

May 29 - June 2, 2023

London, United Kingdom

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Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Cited By

Hosseini HMcGregor ASengupta RVaish RViswanathan VDastani MSichman JAlechina NDignum V(2024)Tight Approximations for Graphical House AllocationProceedings of the 23rd International Conference on Autonomous Agents and Multiagent Systems10.5555/3635637.3662936(825-833)Online publication date: 6-May-2024
https://dl.acm.org/doi/10.5555/3635637.3662936

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