ANASSA paper refines spatial agentic AI framework into low-level architecture

Key points

• Authors Constantinos Papantoniou and Brian Hilton refine the earlier ANASSA framework into an implementation-facing low-level architecture using Design Science Research.
• The design includes 47 logical roles, versioned task graphs, capability-based agent selection, typed contracts, and provenance records.
• The architecture is demonstrated via an end-to-end execution trace and analytically evaluated, not tested in a deployed system.
• It is kept independent of any specific AI model, geospatial platform, communication protocol, or deployment environment.

Why it matters for marketers: Teams building governed geospatial AI agents get a concrete component blueprint covering validation, governance, and recovery paths, though it remains an unimplemented academic design.