SimuLean:面向制造系统设计的开源 3D 智能体离散事件仿真器
Agentic discrete-event simulation for manufacturing system design: an open 3D simulator, a benchmark and an industrial case
AI 导读
西班牙研究团队发布 SimuLean,一个基于 Unity 引擎的开源 3D 离散事件仿真器,专为 AI 智能体编程设计,并提供 18 项制造建模任务的 benchmark。
正文 · 原文
Abstract:The design of manufacturing systems relies on discrete-event simulation (DES) models that experts still build in tool-specific interfaces. AI agents can now write simulation code, but every model they write from scratch is new, unverified software. We present SimuLean, an open-source 3D DES simulator on the Unity engine designed to be programmed by AI agents: its modelling semantics are verified once, in the platform, and the agent builds and studies one model through domain-level commands, in the 3D scene or headless; physically simulated durations are calibrated for fast headless studies. We evaluated it on 18 manufacturing modelling tasks, from single machines to published production lines. A frontier agent built valid models in 93 of 108 attempts (86%), in about two minutes each; on the benchmark's interface version, two frontier agents built 105 of 108 models through domain commands alone, so that each comes with a record of how it was built. Every residual failure was silent - a model that builds and runs but answers wrongly - and only comparison with reference models revealed them all. In an industrial case, one agent working alone rebuilt, verified and studied a robotised welding workshop from a published study, in SimuLean and in SimPy. Comparing them with the published, expert-built model exposed an error in it; against the corrected model, the agent-built models agree within 1%. One agent can already build complete, realistic and traceable models for the design of manufacturing systems; independent reference models are what make them trustworthy.
| Comments: | 55 pages, 15 figures, 8 tables. Software: this https URL (doi:https://doi.org/10.5281/zenodo.23565564) |
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2611.10602 [cs.AI] |
| (or arXiv:2611.10602v2 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2611.10602 arXiv-issued DOI via DataCite |
Submission history
From: Javier Pernas-Álvarez [view email]
[v1]
Sat, 7 Nov 2026 09:12:09 UTC (2,711 KB)
[v2]
Tue, 10 Nov 2026 07:53:28 UTC (2,711 KB)
来源:arXiv cs.AI · arxiv.org