arXiv cs.AI· Surya Shetty, Ulisses Braga-Neto·· 9 天前AI 评分24
LLM-IDEA：可辨识性驱动的实验智能体，自主发现机制世界模型
LLM-IDEA: Identifiability-Driven Experimental Agent for Autonomous Discovery of Mechanistic World Models
AI 导读
研究者提出可辨识性驱动的实验智能体 LLM-IDEA，其可辨识性引擎对实验平台期给出三分类判定：能力上限、设计类内可解、或已证明穷尽。在 ODEBench 上，62 个含自由常数的系统中 60 个在第 0 轮即可辨识，RC 电路被判定为穷尽，收获模型仅需增加一个初始条件即可求解。
正文 · 原文
Abstract:Large language model agents are being increasingly deployed as autonomous scientists, designing experiments and inferring mechanistic world models with minimal human oversight. Yet identifiability is often overlooked: when a plateau is reached, the agent needs to know whether it is not yet capable enough or the model simply is not identifiable from the data, in which case no amount of further experimentation of the same kind can help. We propose the Identifiability-Driven Experimental Agent (LLM-IDEA) for closed-loop discovery with an identifiability engine that returns a three-way plateau verdict: capability limit, resolvable within the design class, or certified exhausted. On ODEBench, 60 of the 62 systems with free constants are identifiable at round 0; the RC circuit is certified exhausted for every experiment that protocol can run, and a harvesting model is resolvable by one added initial condition. The identifiability engine reproduces known verdicts on Lotka-Volterra, Van der Pol, Lorenz, and a pharmacokinetic model, where it recommends the intravenous arm pharmacologists use, and it ranks the depth scorer of our own benchmark last among four observation designs. On the DiscoverPhysics benchmark, it finds two public worlds whose explanation rubric rewards a distinction no legal experiment can make, and every model there with accurate trajectories failed the explanation grade (15 of 15, against 5 of 9 in identifiable worlds, p = 0.012). On the Alien Universe, a two-body testbed we propose in which a force law switches between a provably non-identifiable and an identifiable protocol, LLM-IDEA on the identifiable protocol reaches discovery depth at least three on 8/8 seeds versus 1/8 without it. An autonomous discovery agent can thus compute, rather than guess, whether a plateau calls for more search, a better experiment of the same kind, or a different kind of experiment.
| Subjects: | Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.11253 [cs.AI] |
| (or arXiv:2610.11253v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.11253 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Ulisses Braga-Neto [view email]
[v1]
Thu, 8 Oct 2026 05:01:30 UTC (116 KB)
来源：arXiv cs.AI · arxiv.org