Wireless agentic systems enable agents to autonomously perceive, reason, and act. However, existing works neglect the tight coupling between sensing and control in closed-loop integrated sensing and communication (ISAC) systems. In this paper, we propose an active inference (AIF)-driven wireless agentic system for closed-loop ISAC, which jointly optimizes control and sensing resource allocation via backward--forward message passing on a factor graph. The AIF agent maintains a generative model as a digital twin by integrating a localization model for uncertainty-aware state inference and a localization channel knowledge map (CKM) for approximating observation quality during planning. Simulation results demonstrate that the AIF-enabled agent adaptively allocates sensing resources based on spatially varying channel conditions, achieving superior balance among tracking accuracy, control effort, and sensing resource consumption over baseline strategies.

翻译：无线智能体系统使智能体能够自主感知、推理和行动。然而，现有工作忽略了闭环集成感知与通信（ISAC）系统中感知与控制之间的紧密耦合。本文提出一种由主动推断（AIF）驱动的无线智能体系统用于闭环ISAC，该系统通过在因子图上进行后向-前向消息传递来联合优化控制与感知资源分配。AIF智能体通过集成用于不确定性感知状态推断的定位模型和用于规划过程中观测质量近似的定位信道知识图谱（CKM），将生成模型维护为数字孪生。仿真结果表明，与基准策略相比，AIF使能的智能体能够根据空间变化的信道条件自适应分配感知资源，并在跟踪精度、控制能耗和感知资源消耗之间实现优越平衡。