DiabAgent 发布：用智能体实现血糖生理控制
DiabAgent: Toward Agentic Physiological Control
把 LLM 智能体接上胰岛素泵做血糖控制，SweetBench 有 212 个模拟任务，成绩超过开源方案 OpenAPS，思路挺新颖。
DiabAgent 是一套面向智能体生理控制的研究工具包，由 APC 控制框架、DiabetSim 模拟器和 SweetBench 基准组成。SweetBench 将 32 种场景设计实例化为 212 个血糖控制任务，模拟不同患者的饮食、运动和病情事件。在每小时一次的固定决策间隔下，Claude Opus 5.5 驱动的 APC 取得 COGI 73.5 的成绩，高于开源闭环基线 OpenAPS 的 71.2。消融实验显示个体适应与情境信息能改善血糖控制效果，而将高频规则控制与低频智能体决策结合可平衡控制性能与计算成本。
DiabAgent: Toward Agentic Physiological Control
As pretraining scales, medical language models have advanced rapidly in clinical question answering. Their ability to achieve effective physiological control through sustained intervention still lacks systematic quantitative evaluation. Type 1 diabetes provides a concrete setting: impaired insulin secretion creates dependence on exogenous insulin, with dosing continually adjusted using information about meals, exercise, illness, and glucose measurements. We introduce DiabAgent, a research suite for agentic physiological control comprising the Agentic Physiological Control (APC) framework, the DiabetSim simulator, and the SweetBench benchmark. APC controls glucose through medical-device tools, using ongoing observations to infer individual states, accumulate personal experience, and choose treatment actions. We build DiabetSim to simulate different patients, events, and device conditions for scalable virtual testing and training. Using DiabetSim, we construct SweetBench by instantiating 32 scenario designs as 212 glucose-control tasks. With Claude Opus 5.5 and a fixed decision interval of one hour, APC achieves a COGI of 73.5, compared with 71.2 for the open-source closed-loop baseline OpenAPS. Ablations further show that individual adaptation and contextual information improve glucose control. Combining high-frequency rule-based control with lower-frequency agent decisions shows potential for balancing control performance and computational cost. Our work provides a framework, simulator, and evaluation foundation for agents to participate in human physiological control.