Asynchronous Proportional Response Dynamics: Convergence in Markets with Adversarial Scheduling

Yoav Kolumbus, Menahem Levy, N. Nisan
4/5/2026

No confident code implementation found for this paper.

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.

DOISemantic Scholar

Code Implementations

No confident code match yet

We couldn't find an author-owned or strongly-evidenced community implementation for this paper. Any repos shown below are weak matches — verify before relying on them.

No code implementations found yet.

Know of an implementation? Let us know in the comments below!

Cite this paper

@article{kolumbus2026asynchronous,
  title  = {Asynchronous Proportional Response Dynamics: Convergence in Markets with Adversarial Scheduling},
  author = {Yoav Kolumbus and Menahem Levy and N. Nisan},
  year   = {2026},
  doi    = {10.52202/075280-1104},
  url    = {https://doi.org/10.52202/075280-1104},
  journal = {Neural Information Processing Systems}
}

Discussion