Graphical House Allocation

• URL: http://arxiv.org/abs/2301.01323v2
• Date: Mon, 18 Sep 2023 23:37:38 GMT
• Title: Graphical House Allocation
• Authors: Hadi Hosseini, Justin Payan, Rik Sengupta, Rohit Vaish and Vignesh Viswanathan
• Abstract summary: A key criterion in such problems is satisfying some fairness constraints such as envy-freeness. Our goal is to minimize the aggregate envy among the agents as a natural fairness objective. 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.
• Score: 18.119269486735245
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The classical house allocation problem involves assigning $n$ houses (or items) to $n$ agents according to their preferences. A key criterion 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 all pairwise envy values 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, and 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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