dorsal/arxiv
View SchemaFrom Queues to Crowd Flows: Reflected Diffusion Limits for Controlled Agents
| Authors | Thoa Thieu, Roderick Melnik |
|---|---|
| Categories | |
| ArXiv ID | 2601.05895vv1 |
| URL | https://arxiv.org/abs/2601.05895 |
| License | http://arxiv.org/licenses/nonexclusive-distrib/1.0/ |
Abstract
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.
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"abstract": "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.",
"arxiv_id": "2601.05895",
"authors": [
"Thoa Thieu",
"Roderick Melnik"
],
"categories": [
"math.PR"
],
"license": "http://arxiv.org/licenses/nonexclusive-distrib/1.0/",
"title": "From Queues to Crowd Flows: Reflected Diffusion Limits for Controlled Agents",
"url": "https://arxiv.org/abs/2601.05895",
"version": "v1"
},
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