Federation of Agents: Semantics-Aware, Large-Scale Communication Fabric (arxiv.org)

Researchers introduced Federation of Agents (FoA), a distributed orchestration framework that turns static multi-agent pipelines into dynamic, capability-driven collaborations. FoA centers on Versioned Capability Vectors (VCVs) — machine-readable profiles encoding an agent’s skills, costs, and limits as semantic embeddings — making agents discoverable and comparable. The architecture pairs semantic routing (matching tasks to agents via sharded HNSW indices) with cost-biased optimization to enforce operational constraints, and runs over MQTT pub-sub for scalable message passing. Key runtime features include consensus-based dynamic task decomposition (agents collaboratively split tasks into DAGs), plus smart clustering that forms temporary collaborative channels for k-round refinement before final synthesis. Technically, FoA achieves sub-linear coordination complexity through hierarchical capability matching and efficient index maintenance, enabling horizontal scaling across heterogeneous agent federations. In evaluations on HealthBench, FoA delivered ~13× improvement over single-model baselines, with clustering-enhanced collaboration especially effective for complex reasoning that benefits from multiple perspectives. For the AI/ML community this suggests a practical path to unlock collective intelligence: modular, searchable agent marketplaces, cost-aware routing, and structured multi-agent workflows that improve efficiency and solution quality for large-scale, multi-capability problems.