Equilibria in Two-Stage Facility Location with Atomic Clients

Simon Krogmann, Pascal Lenzner, Alexander Skopalik, Marc Uetz, Marnix C. Vos

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
41 Downloads (Pure)

Abstract

We consider competitive facility location as a two-stage multi-agent system with two types of clients. For a given host graph with weighted clients on the vertices, first facility agents strategically select vertices for opening their facilities. Then, the clients strategically select which of the opened facilities in their neighborhood to patronize. Facilities want to attract as much client weight as possible, clients want to minimize congestion on the chosen facility. All recently studied versions of this model assume that clients can split their weight strategically. We consider clients with unsplittable weights but allow mixed strategies. So clients may randomize over which facility to patronize. Besides modeling a natural client behavior, this subtle change yields drastic changes, e.g., for a given facility placement, qualitatively different client equilibria are possible. As our main result, we show that pure subgame perfect equilibria always exist if all client weights are identical. For this, we use a novel potential function argument, employing a hierarchical classification of the clients and sophisticated rounding in each step. In contrast, for non-identical clients, we show that deciding the existence of even approximately stable states is computationally intractable. On the positive side, we give a tight bound of 2 on the price of anarchy which implies high social welfare of equilibria, if they exist.

Original languageEnglish
Title of host publicationProceedings of the 33rd International Joint Conference on Artificial Intelligence, IJCAI 2024
EditorsKate Larson
PublisherInternational Joint Conferences on Artificial Intelligence
Pages2842-2850
Number of pages9
ISBN (Electronic)9781956792041
DOIs
Publication statusPublished - 2024
Event33rd International Joint Conferences on Artificial Intelligence, IJCAI 2024 - Jeju Island, Korea, Republic of
Duration: 19 Aug 202425 Aug 2024
Conference number: 33

Publication series

NameIJCAI International Joint Conference on Artificial Intelligence
ISSN (Print)1045-0823

Conference

Conference33rd International Joint Conferences on Artificial Intelligence, IJCAI 2024
Abbreviated titleIJCAI 2024
Country/TerritoryKorea, Republic of
CityJeju Island
Period19/08/2425/08/24

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