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Computer Science > Computer Science and Game Theory

arXiv:2012.00689 (cs)
[Submitted on 1 Dec 2020 (v1), last revised 10 Jan 2021 (this version, v3)]

Title:Dynamic Weighted Matching with Heterogeneous Arrival and Departure Rates

Authors:Natalie Collina, Nicole Immorlica, Kevin Leyton-Brown, Brendan Lucier, Neil Newman
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Abstract:We study a dynamic non-bipartite matching problem. There is a fixed set of agent types, and agents of a given type arrive and depart according to type-specific Poisson processes. Agent departures are not announced in advance. The value of a match is determined by the types of the matched agents. We present an online algorithm that is (1/8)-competitive with respect to the value of the optimal-in-hindsight policy, for arbitrary weighted graphs. Our algorithm treats agents heterogeneously, interpolating between immediate and delayed matching in order to thicken the market while still matching valuable agents opportunistically.
Subjects: Computer Science and Game Theory (cs.GT); Data Structures and Algorithms (cs.DS)
Cite as: arXiv:2012.00689 [cs.GT]
  (or arXiv:2012.00689v3 [cs.GT] for this version)
  https://doi.org/10.48550/arXiv.2012.00689
arXiv-issued DOI via DataCite

Submission history

From: Brendan Lucier [view email]
[v1] Tue, 1 Dec 2020 17:49:53 UTC (29 KB)
[v2] Mon, 7 Dec 2020 15:52:12 UTC (29 KB)
[v3] Sun, 10 Jan 2021 23:07:48 UTC (31 KB)
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Nicole Immorlica
Kevin Leyton-Brown
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