Cognitive sovereignty in 6G: architecting a Neuro-Symbolic knowledge plane for verifiable agentic automation

This paper proposes a cognitive sovereignty architecture for sixth Generation (6G) networks based on a Neuro-Symbolic Knowledge Plane (NSKP) and Large Action Models (LAMs). Unlike traditional knowledge planes that serve as static information repositories, the proposed NSKP integrates neural intuition with symbolic rigor to enable verifiable reasoning. The NSKP maintains a unified knowledge graph with logical constraints, while LAMs translate high-level intents into verifiable network actions. To support distributed operation under locality and privacy constraints, we introduce a federated causal discovery algorithm that learns a global causal graph from edge telemetry without moving raw data. Synthetic experiments show that Fed-DAG recovers causal structure close to a centralised upper bound, provides clear gains for causal root cause analysis over correlation and topology based baselines, and maintains accuracy under sparse gradient communication. The results demonstrate that a neuro-symbolic control layer can deliver agentic yet verifiable automation for 6G management.