Ceylan, E., Chen, J. and Roy, S. orcid.org/0000-0003-3633-542X (2023) Optimal Seat Arrangement: What Are the Hard and Easy Cases? In: Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence. Thirty-Second International Joint Conference on Artificial Intelligence {IJCAI-23}, 19-25 Aug 2023, Macao, S.A.R. International Joint Conferences on Artificial Intelligence Organization , pp. 2563-2571.
Abstract
We study four NP-hard optimal seat arrangement problems which each have as input a set of n agents, where each agent has cardinal preferences over other agents, and an n-vertex undirected graph (called the seat graph). The task is to assign each agent to a distinct vertex in the seat graph such that either the sum of utilities or the minimum utility is maximized, or it is envy-free or exchange-stable. Aiming at identifying hard and easy cases, we extensively study the algorithmic complexity of the four problems by looking into natural graph classes for the seat graph (e.g., paths, cycles, stars, or matchings), problem-specific parameters (e.g., the number of non-isolated vertices in the seat graph or the maximum number of agents towards whom an agent has non-zero preferences), and preference structures (e.g., non-negative or symmetric preferences). For strict preferences and seat graphs with disjoint edges and isolated vertices, we correct an error in the literature and show that finding an envy-free arrangement remains NP-hard in this case.
Metadata
Item Type: | Proceedings Paper |
---|---|
Authors/Creators: |
|
Keywords: | Game Theory and Economic Paradigms: GTEP: Computational social choice; Game Theory and Economic Paradigms: GTEP: Cooperative games; Game Theory and Economic Paradigms: GTEP: Fair division |
Dates: |
|
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: | 15 Feb 2024 11:16 |
Last Modified: | 15 Feb 2024 11:16 |
Status: | Published |
Publisher: | International Joint Conferences on Artificial Intelligence Organization |
Identification Number: | 10.24963/ijcai.2023/285 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:209177 |