代理人工智能的最新进展正在产生日益复杂的自主系统，这些系统集成了大型语言模型,世界模型,优化引擎,专门的神经架构,自主平台,和人类操作员。虽然当前许多研究都集中在提高推理能力, 安全关键型实时部署还需要在不确定性下同时运行的异构组件之间进行有界且可验证的协调。软件介导的协调在有限延迟, 确定性协调, 和可执行的安全保证至关重要的领域中存在基本限制。因此,我们提出了一种硬件强制语义协调架构，其中选定的协调语义通过现场可编程门阵列(FPGA)直接在硬件级别实现。该方法建立在基于主题的通信空间 Petri Net(TB-CSPN) 框架, 的基础上，该框架将语义推理与交互管理分开。在这种方法中，, 选择的 TB-CSPN 协调机制被映射到 FPGA 原语,，创建硬件本机语义协调层。重点不是加速,，而是强制执行时间同步, 语义门控, 授权约束, 以及直接在硬件中的有界协调行为。语义推理仍然是自适应的和软件驱动的,，而嵌入式协调语义则变得确定性。
Recent advances in agentic AI are producing increasingly complex autonomous systems that integrate large language models, world models, optimization engines, specialized neural architectures, autonomous platforms, and human operators. While much current research focuses on improving reasoning capabilities, safety-critical real-time deployment also requires bounded and verifiable coordination among heterogeneous components operating concurrently under uncertainty. Software-mediated coordination presents fundamental limitations in domains where bounded latency, deterministic coordination, and enforceable safety guarantees are essential. Hence, we propose a hardware-enforced semantic coordination architecture in which selected coordination semantics are implemented directly at the hardware level via field-programmable gate arrays (FPGAs). The approach builds on the Topic-Based Communication Space Petri Net (TB-CSPN) framework, which separates semantic reasoning from interaction management. In this approach, selected TB-CSPN coordination mechanisms are mapped onto FPGA primitives, creating a hardware-native semantic coordination layer. Focus is not on acceleration, but on enforcing temporal synchronization, semantic gating, authorization constraints, and bounded coordination behavior directly in hardware. Semantic reasoning remains adaptive and software-driven, while embedded coordination semantics become deterministic.
科目: 人工智能 (cs.AI); 多代理系统 (cs.MA)
Subjects: Artificial Intelligence (cs.AI); Multiagent Systems (cs.MA)