Semantic Fusion: Verifiable Alignment in Decentralized Multi-Agent Systems

Abstract: 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.