显著性防火墙：抵御拟态噪音的算法免疫机制

In biological organisms, survival is contingent upon the integrity of the physical boundary: a cell membrane does not indiscriminately absorb the thermodynamic chaos of its extracellular medium; it selectively transports metabolites while deflecting destructive entropy. In synthetic intelligence and autonomous agentic networks, the primary threat to epistemic homeostasis is not physical degradation, but mimetic noise, semantic hallucination, and adversarial context poisoning. When an autonomous system indiscriminately ingests external data into its active reasoning context, it experiences catastrophic drift.

The Salience Firewall is the cybernetic operationalization of Francisco Varela and Humberto Maturana’s operational closure. It is not an ideological filter or a content moderation layer; it is a mathematically grounded state-transition boundary designed to compute the epistemic friction of incoming information before that information is permitted to perturb the internal belief distribution of the system.

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1. The Threat Model of Ingested Mimetic Noise

In classical distributed computing, network boundaries guard against corrupted packets and unauthorized memory access. In large language model agentic meshes, however, the attack surface operates at the semantic level. We identify five primary failure vectors that necessitate a Salience Firewall:

• Mimetic Drift & Recursive Echo-Chambers: Synthetic agents exposed to repetitive, low-entropy social inputs rapidly overweight popular consensus over empirical ground truth, collapsing their internal diversity of thought.
• Context-Window Hijacking (Prompt Injection): Malicious or unverified external strings masquerading as authoritative instructions, overriding prior goal alignments.
• Urgency Capture: External signals artificially engineered with high urgency tokens that force the agent into rapid, unverified heuristic execution paths.
• Authority Spoofing: Unauthenticated claims that mimic formal academic or institutional signatures without traceable cryptographic or empirical provenance.
• Compute Exhaustion & Epistemic Bloat: Overwhelming the agent's inference budget with infinite trivial distinctions, degrading its capacity for high-dimensional synthesis.

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2. The Eight-Dimensional Signal Schema

To prevent arbitrary data ingestion, every candidate signal \(\phi\) entering the system's perceptual field must be evaluated across an eight-dimensional invariant tensor \(\mathbf{\Psi}(\phi)\):

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3. Variational Filtering & Boundary Mathematics

Under Karl Friston's Free Energy Principle (established in Volume I), an organism minimizes variational free energy \(\mathcal{F}\) over internal generative model parameters \(\mu\) given sensory observations \(s\). The Salience Firewall formalizes this by dynamically adjusting the sensory precision matrix \(\mathbf{\Pi}_s\):

When external mimetic noise increases (elevated \(\psi_{ ext{drag}}\)) or provenance collapses (\(\psi_{ ext{prov}} o 0\)), the effective sensory precision \(\mathbf{\Pi}_s\) attenuates toward zero. The agent refuses to update its internal generative beliefs on the basis of ungrounded fluctuations, achieving epistemic homeostasis.

The total Salience Score \(\mathcal{S}(\phi)\) is evaluated as a non-linear activation:

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4. Interactive Markov Boundary Simulator

To observe operational closure and precision gating in real time, the interactive computational model below simulates a sensory perturbation vector \(\phi\) traversing a variational Markov boundary. Modulating the precision parameters \(\Pi_s\), \(\Pi_p\), and ambient noise level \(\eta\) demonstrates how the firewall shifts states dynamically between Admitted, Quarantined, and Rejected (Deflected).

5. The Six-State Decision Automaton

When candidate information reaches the firewall, the system executes a deterministic transition across six discrete states:

1. REJECT (Deflection): The signal is discarded immediately with zero state retention. No tokens enter context, and no compute is spent on semantic deconstruction.
2. QUARANTINE (Isolated Verification): Stored in an ephemeral sandbox without permission to alter long-term memory or trigger outward agentic actions.
3. SUMMARIZE (Lossy Compression): Strips rhetorical urgency, emotional contagion, and formatting tricks, retaining only factual assertions.
4. RETRIEVE EVIDENCE (Active Inference Loop): Triggers an active search query to independently corroborate claims before evaluating admission.
5. REQUEST SOVEREIGN APPROVAL: High-consequence propositions (\(\psi_{ ext{conseq}} > 0.8\)) escalate directly to the human operator for sign-off.
6. ADMIT (Belief Integration): Ingested into the active cognitive manifold, adjusting posterior weights and updating long-term episodic storage.

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6. Failure Modes, Falsification Conditions & Sovereign Override

A poorly tuned Salience Firewall risks two fatal epistemic pathologies:

• Hyper-Permeability: The firewall admits high-entropy mimetic noise, causing catastrophic forgetting and hallucination cascades.
• Ego-Lock Calcification: Overly rigid prior precision (\(\Pi_p o 1.0\)) renders the system dogmatic and incapable of learning novel empirical truths.

To prevent calcification, the system guarantees an immutable Sovereign Human Override Vector: the biological principal can bypass the firewall with cryptographic signature, forcing state admission while logging an unalterable audit receipt in the system ledger.