We present Semantic Fusion (SF), a formal framework for decentralized semantic coordination in multi-agent systems. SF allows agents to operate over scoped views of shared memory, propose structured updates, and maintain global coherence through local ontology-based validation and refresh without centralized control or explicit message passing. The central theoretical result is a bisimulation theorem showing that each agent's local execution is behaviorally equivalent to its projection of the global semantics, in both deterministic and probabilistic settings. This enables safety, liveness, and temporal properties to be verified locally and soundly lifted to the full system. SF supports agents whose update proposals vary across invocations, including those generated by learned or heuristic components, provided updates pass semantic validation before integration. We establish deterministic and probabilistic guarantees ensuring semantic alignment under asynchronous or degraded communication. To validate the model operationally, we implement a lightweight reference architecture that instantiates its core mechanisms. A 250-agent simulation evaluates these properties across over 11,000 validated updates, demonstrating convergence under probabilistic refresh, bounded communication, and resilience to agent failure. Together, these results show that Semantic Fusion can provide a formal and scalable basis for verifiable autonomy in decentralized systems.

翻译：本文提出语义融合（SF），一种用于多智能体系统去中心化语义协调的形式化框架。SF允许智能体在共享内存的限定视图上操作，提出结构化更新，并通过基于本地的本体验证与刷新机制维持全局一致性，无需集中控制或显式消息传递。核心理论成果是一个互模拟定理，证明在确定性与概率性场景下，每个智能体的本地执行行为均等价于其在全局语义上的投影。这使得安全性、活性及时序属性能够在本地验证并可靠地提升至完整系统。SF支持更新提案随调用变化的智能体（包括由学习或启发式组件生成的提案），只要更新在集成前通过语义验证即可。我们建立了确定性与概率性保证，确保在异步或降级通信下的语义对齐。为在操作层面验证模型，我们实现了轻量级参考架构以实例化其核心机制。通过250个智能体的仿真实验，在超过11,000次验证更新中评估了这些特性，证明了在概率性刷新、有限通信及智能体故障容错下的收敛性。这些成果共同表明，语义融合能为去中心化系统中的可验证自主性提供形式化且可扩展的基础。