SPFR: Semantic Potential Field Routing for the Distributed Internet of Agents

Abstract

In a distributed Internet of Agents (IoA) without centralized routing control, routing tasks to capability-matched executors is challenging because destinations are not predetermined and agents have bounded local service views. Discover-then-forward approaches, by contrast, select an executor before network forwarding and therefore do not directly support reselection when additional candidates become visible downstream. We introduce Semantic Potential Field Routing (SPFR), a distributed IoA routing algorithm that integrates executor discovery and reselection into hop-by-hop forwarding. SPFR represents each executor visible in a local semantic forwarding information base (FIB) as a task-conditioned semantic potential source, with utility setting its strength and hop distance inducing exponential attenuation. At each hop, the forwarding agent recomputes these potentials, reselects the dominant executor, and forwards the task one hop toward it. Under task-consistent frozen-FIB conditions, we prove loop freedom and finite-hop termination and derive an explicit additive error bound under bounded visibility relative to the full-visibility objective. Extensive simulations on real-world topologies show that SPFR approaches the realized utility of distributed utility-greedy routing and request-triggered global discovery while using fewer forwarding hops and substantially fewer request-triggered messages, and remains robust under network and service dynamics.