Enabling Long-term Fairness in Dynamic Resource Allocation

Tareq Si Salem, Georgios Iosifidis, Giovanni Neglia

Research output: Contribution to journalArticleScientificpeer-review

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Abstract

We study the fairness of dynamic resource allocation problem under the α-fairness criterion. We recognize two different fairness objectives that naturally arise in this problem: the well-understood slot-fairness objective that aims to ensure fairness at every timeslot, and the less explored horizon-fairness objective that aims to ensure fairness across utilities accumulated over a time horizon. We argue that horizon-fairness comes at a lower price in terms of social welfare. We study horizon-fairness with the regret as a performance metric and show that vanishing regret cannot be achieved in presence of an unrestricted adversary. We propose restrictions on the adversary's capabilities corresponding to realistic scenarios and an online policy that indeed guarantees vanishing regret under these restrictions.

Original languageEnglish
Pages (from-to)31-32
Number of pages2
JournalPerformance Evaluation Review
Volume51
Issue number1
DOIs
Publication statusPublished - 2023

Bibliographical note

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Keywords

  • axiomatic bargaining
  • dynamic resource allocation
  • multi-timescale fairness
  • online learning

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