An Improved 2-Agent Kidney Exchange Mechanism

Caragiannis, Ioannis; Filos-Ratsikas, Aris; Procaccia, Ariel D.

doi:10.1007/978-3-642-25510-6_4

Cited by 13 publications

(6 citation statements)

References 13 publications

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“…Much of the theoretical market design work in kidney exchange uses the ABO-model, which labels vertices in a compatibility graph with their patient and donor blood types (see, e.g., [3,6,11,14,25,27]). Work in this model has not directly addressed sensitization.…”

Section: Model With Abo-blood Types and Two Levels Of Sensitizationmentioning

confidence: 99%

“…They provide a wealth of opportunities for theoretical and experimental research in both fields. For instance, key questions in practically tractable clearing algorithms [7,13,14,15] and mechanism design [3,5,6,11] remain unsolved. Advances in these areas will benefit the greater artificial intelligence community immensely, and provide valuable experience in fielding real-world artificial intelligence technology.…”

Section: Introductionmentioning

confidence: 99%

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Price of Fairness in Kidney Exchange.

2014

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Kidney exchange provides a life-saving alternative to long waiting lists for patients in need of a new kidney. Fielded exchanges typically match under utilitarian or near-utilitarian rules; this approach marginalizes certain classes of patients. In this paper, we focus on improving access to kidneys for highly-sensitized, or hard-tomatch, patients. Toward this end, we formally adapt a recently introduced measure of the tradeoff between fairness and efficiencythe price of fairness-to the standard kidney exchange model. We show that the price of fairness in the standard theoretical model is small. We then introduce two natural definitions of fairness and empirically explore the tradeoff between matching more hard-tomatch patients and the overall utility of a utilitarian matching, on real data from the UNOS nationwide kidney exchange and simulated data from each of the standard kidney exchange distributions.

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Section: Model With Abo-blood Types and Two Levels Of Sensitizationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Price of Fairness in Kidney Exchange.

2014

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“…-In practice kidney exchanges weight edges according to the quality of the fit (for example an edge between an old donor and young patient would have low weight). While weights are not taken into account in most existing kidney exchange papers (see, e.g., [Ashlagi et al 2010;Toulis and Parkes 2011;Ashlagi and Roth 2011;Caragiannis et al 2011;Ashlagi et al 2012]), they do play a role in the recent work of Bansal et al [2012]. A related extension has to with assigning a different prob-…”

Section: Discussionmentioning

confidence: 99%

Harnessing the power of two crossmatches

Blum¹,

Gupta²,

Procaccia³

et al. 2013

Proceedings of the Fourteenth ACM Conference on Electronic Commerce

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Kidney exchanges allow incompatible donor-patient pairs to swap kidneys, but each donation must pass three tests: blood, tissue, and crossmatch. In practice a matching is computed based on the first two tests, and then a single crossmatch test is performed for each matched patient. However, if two crossmatches could be performed per patient, in principle significantly more successful exchanges could take place. In this paper, we ask: If we were allowed to perform two crossmatches per patient, could we harness this additional power optimally and efficiently? Our main result is a polynomial time algorithm for this problem that almost surely computes optimal -up to lower order terms -solutions on random large kidney exchange instances.

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“…If our objective is to minimize the sum of the agent's costs, known as the social cost, then we are looking for strategyproof mechanisms that achieve a social cost as close as possible to that of the optimal mechanism, which need not be strategyproof. The prominent measure of performance for mechanisms in computer science literature is the approximation ratio [2,6,12,24], i.e. the worst possible ratio of the social cost achieved by the mechanism over the minimum social cost over all instances of the problem.…”

Section: Introductionmentioning

confidence: 99%

Facility location with double-peaked preferences

Filos-Ratsikas

Zhang

et al. 2017

Auton Agent Multi-Agent Syst

Self Cite

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We study the problem of locating a single facility on a real line based on the reports of self-interested agents, when agents have double-peaked preferences, with the peaks being on opposite sides of their locations. We observe that double-peaked preferences capture reallife scenarios and thus complement the well-studied notion of single-peaked preferences. As a motivating example, assume that the government plans to build a primary school along a street; an agent with single-peaked preferences would prefer having the school built exactly next to her house. However, while that would make it very easy for her children to go to school, it would also introduce several problems, such as noise or parking congestion in the morning. A 5-min walking distance would be sufficiently far for such problems to no longer be much of a factor and at the same time sufficiently close for the school to be easily accessible by the children on foot. There are two positions (symmetrically) in each direction and those would be the agent's two peaks of her double-peaked preference. Motivated by natural scenarios like the one described above, we mainly focus on the case where peaks are equidistant from the agents' locations and discuss how our results extend to more general settings. We show that most of the results for single-peaked preferences do not directly apply to this setting, which makes the problem more challenging. As our main contribution, we present a simple truthfulin-expectation mechanism that achieves an approximation ratio of 1 + b/c for both the social and the maximum cost, where b is the distance of the agent from the peak and c is the minimum cost of an agent. For the latter case, we provide a 3/2 lower bound on the approximation ratio of any truthful-in-expectation mechanism. We also study deterministic mechanisms under some natural conditions, proving lower bounds and approximation guarantees. We prove that among a large class of reasonable strategyproof mechanisms, there is no deterministic mechanism that outperforms our truthful-in-expectation mechanism. In order to obtain this result, we first characterize mechanisms for two agents that satisfy two simple properties; we use the same characterization to prove that no mechanism in this class can be groupstrategyproof.

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An Improved 2-Agent Kidney Exchange Mechanism

Cited by 13 publications

References 13 publications

Price of Fairness in Kidney Exchange.

Price of Fairness in Kidney Exchange.

Harnessing the power of two crossmatches

Facility location with double-peaked preferences

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