发表机构
University of Bologna; Technology Innovation Institute (TII)（博洛尼亚大学; 技术创新研究院（TII））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对分布式无人机集群中上下文退化和通信开销问题，提出基于事件驱动生命周期、原子笔记记忆和兴趣感知八卦引擎的SLM架构，在模拟搜救中实现全部任务完成并减半推理消耗。
AI 中文摘要
无人机集群在不确定环境中日益依赖语言模型智能体来提供自适应的任务级推理。完全分布式控制中，每架无人机搭载独立的小型语言模型（SLM），消除了对集中式协调器的依赖，但引入了信息管理问题：长时间运行的交互历史会降低推理上下文质量，而不加区分的信息传播会增加通信和推理开销。我们通过一种分布式无人机智能体架构解决这些挑战，该架构通过事件驱动的推理-行动-观察生命周期实现连续的本地SLM控制。运行时知识被表示为结构化的原子笔记，并组织为核心记忆、本地记忆和特定对等记忆。一种确定性的兴趣感知八卦引擎根据接收者特定的语义新颖性和时效性选择性传播这些笔记。我们使用十架无人机在模拟搜救任务中评估该架构。我们的方法完成了所有实验运行，而无限制的泛洪消息仅完成70-85%，将转发决策委托给SLM则导致每次运行均无法完成任务。与无限制泛洪相比，我们的方法将推理令牌消耗大约减半，减少了传输数据，并实现了更低的幸存者计数误差。
英文摘要
Unmanned aerial vehicle (UAV) swarms increasingly rely on language-model agents to provide adaptive mission-level reasoning in uncertain environments. Fully distributed control, in which each UAV hosts an independent Small Language Model (SLM), removes reliance on a centralized coordinator but introduces an information-management problem: long-running interaction histories can degrade the reasoning context, while indiscriminate information dissemination increases communication and inference overhead. We address these challenges with a distributed UAV-agent architecture that enables continuous local SLM control through an event-driven reason-act-observe lifecycle. Runtime knowledge is represented as structured atomic notes and organized into core, local, and peer-specific memory. A deterministic interest-aware gossip engine selectively disseminates these notes according to recipient-specific semantic novelty and recency. We evaluate the architecture using ten UAVs in a simulated search-and-rescue mission. Our approach completes all experimental runs, whereas unrestricted flooding messages completes only 70-85\%, and delegating forwarding decisions to the SLM prevents mission completion in every run. Compared with unrestricted flooding, our approach approximately halves inference-token consumption, reduces transmitted data, and achieves lower survivor-count error.
Comments12 pages, 4 figures. This paper has been accepted for presentation at the 24th IEEE Consumer Communications & Networking Conference 2027 (CCNC 2027)
