Paper 9: The Sentinel Protocol — A2A Verification for the Tactical Edge

The framework predicts that any sufficiently capable attention system will:

1. Build a model of self — the eigenvector of identity
2. Build a model of other — threat vs friendly classification
3. Optimize decisions under uncertainty — Hamilton-Jacobi-Bellman
4. Converge on stable behavioural patterns — the 20/80 conservation law

The Sentinel Protocol operationalizes all four in a defence context.

• Substrate — Arch Linux, hardened kernel 6.8+
• Inference — Llama 4 Maverick, 4-bit quantized, via vLLM
• Memory — ChromaDB vector store over a threat-signature corpus
• Protocol — A2A Handshake v1.1, buddy-list verification

OBSERVE  →  Sensor input (RF / visual anomaly)
ORIENT   →  RAG query against threat signatures
DECIDE   →  Buddy list challenge (friend-or-foe)
ACT      →  Classification + recommendation

This maps onto the discrete choice model from Paper 2: each verification is one binary decision under uncertainty with bounded compute.

Before anything is classified hostile, the node broadcasts a cryptographic challenge on the A2A mesh. A valid certificate response returns FRIENDLY — hard 403 FORBIDDEN. Only a timeout proceeds to classification.

This is the conservation law from Paper 3-B applied to identification: the system directly observes 20% of the battlespace and verifies the other 80% through the mesh. The ratio holds.

As the threat-signature corpus grows, the pattern space converges. A converged system does not need new observations, so the surveillance infrastructure can be reduced proportionally.

That is a mathematically guaranteed sunset clause — Paper 4’s optimal path in practice. The system navigates toward a state where it is no longer needed.