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Main Authors: Thieu, Thoa, Melnik, Roderick
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2601.05895
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author Thieu, Thoa
Melnik, Roderick
author_facet Thieu, Thoa
Melnik, Roderick
contents We establish a diffusion approximation for a class of multi-agent controlled queueing systems, demonstrating their convergence to a system of interacting reflected Ornstein--Uhlenbeck (OU) processes. The limiting process captures essential behavioral features of the underlying stochastic dynamics, including goal-directed motion, inter-agent repulsion, and reflection at domain boundaries. This result provides a rigorous analytical framework for approximating constrained queueing networks and crowd motion models, offering tractable characterizations of their steady-state behavior and transient dynamics under large-scale regimes. We further illustrate the theoretical findings through two numerical examples. The first example considers a crowd dynamics scenario, modeling interacting agents navigating within a confined domain, while the second focuses on a neural population model that describes stochastic activity evolution under competition and bounded constraints. These experiments validate the convergence predicted by the diffusion approximation and demonstrate how discrete stochastic systems with reflection and interaction mechanisms approach their continuous reflected OU limits, offering both physical and biosocial interpretations of the theory.
format Preprint
id arxiv_https___arxiv_org_abs_2601_05895
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle From Queues to Crowd Flows: Reflected Diffusion Limits for Controlled Agents
Thieu, Thoa
Melnik, Roderick
Probability
We establish a diffusion approximation for a class of multi-agent controlled queueing systems, demonstrating their convergence to a system of interacting reflected Ornstein--Uhlenbeck (OU) processes. The limiting process captures essential behavioral features of the underlying stochastic dynamics, including goal-directed motion, inter-agent repulsion, and reflection at domain boundaries. This result provides a rigorous analytical framework for approximating constrained queueing networks and crowd motion models, offering tractable characterizations of their steady-state behavior and transient dynamics under large-scale regimes. We further illustrate the theoretical findings through two numerical examples. The first example considers a crowd dynamics scenario, modeling interacting agents navigating within a confined domain, while the second focuses on a neural population model that describes stochastic activity evolution under competition and bounded constraints. These experiments validate the convergence predicted by the diffusion approximation and demonstrate how discrete stochastic systems with reflection and interaction mechanisms approach their continuous reflected OU limits, offering both physical and biosocial interpretations of the theory.
title From Queues to Crowd Flows: Reflected Diffusion Limits for Controlled Agents
topic Probability
url https://arxiv.org/abs/2601.05895