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Asynchronous Proportional Response Dynamics: Convergence in Markets with Adversarial Scheduling

Yoav Kolumbus, Menahem Levy, Noam Nisan

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

Abstract

We study Proportional Response Dynamics (PRD) in linear Fisher markets, where participants act asynchronously. We model this scenario as a sequential process in which at each step, an adversary selects a subset of the players to update their bids, subject to liveness constraints. We show that if every bidder individually applies the PRD update rule whenever they are included in the group of bidders selected by the adversary, then, in the generic case, the entire dynamic converges to a competitive equilibrium of the market. Our proof technique reveals additional properties of linear Fisher markets, such as the uniqueness of the market equilibrium for generic parameters and the convergence of associated no swap regret dynamics and best response dynamics under certain conditions.

Original languageEnglish
Title of host publicationAdvances in Neural Information Processing Systems 36 - 37th Conference on Neural Information Processing Systems, NeurIPS 2023
EditorsA. Oh, T. Neumann, A. Globerson, K. Saenko, M. Hardt, S. Levine
ISBN (Electronic)9781713899921
StatePublished - 2023
Event37th Conference on Neural Information Processing Systems, NeurIPS 2023 - New Orleans, United States
Duration: 10 Dec 202316 Dec 2023

Publication series

NameAdvances in Neural Information Processing Systems
Volume36

Conference

Conference37th Conference on Neural Information Processing Systems, NeurIPS 2023
Country/TerritoryUnited States
CityNew Orleans
Period10/12/2316/12/23

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Information Systems
  • Signal Processing

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