# DARPA CLARA TA1 Technical Volume: Aevion Neuroplastic World-Model Architecture

## 1. Problem Statement
Existing autonomous world models (e.g., V-JEPA 2, Genie 3) exhibit remarkable predictive and simulation capabilities but lack **Certifiable Governance**. In mission-critical defense settings, black-box agentic behavior introduces unquantifiable risks—specifically, the inability to guarantee that an action trajectory remains within an admissible control manifold under distribution shift. Current "Type-2" reasoning narratives remain fundamentally unverified, providing audit logs that are merely textual traces rather than machine-checkable mathematical proofs.

## 2. Technical Approach: The Type-2 Proof
Aevion proposes a **Neuroplastic World-Model** architecture that integrates a predictive latent core with a deterministic **Koopman Governance Overlay**.

### 2.1 Predictive Substrate
The system utilizes a dual-pathway latent prediction engine (VLA-JEPA derivative) for abstract world-dynamics learning. The model is "neuroplastic," updating its internal structure to maintain predictive accuracy as environmental dynamics shift.

### 2.2 Koopman Governance Layer (The Digital Brainstem)
To provide certifiable safety, we utilize an **NN-ResDMD** estimator to approximate the Koopman operator of the hidden-state dynamics.
- **Stability Monitoring:** We track the spectral radius $\rho(\hat{K})$ online. If $\rho$ crosses the stability threshold (1.0589), a **Constitutional Halt** is triggered.
- **Dissipativity Constraints:** Learned operators are projected into a provably stable set using LMI-based parameter perturbations, ensuring grounded behavior.
- **Residual Gating:** $3\sigma$ anomaly detection on spectral residuals catches model drift before it compromises safety.

## 3. Innovations & Technical Differentiation
1. **Grounded Operator Theory:** Unlike heuristic guardrails, Aevion uses operator-theoretic estimators (POWR, NN-ResDMD) for closed-form action-value and stability analysis.
2. **VULCAN JET Routing:** Automated LLM-driven synthesis of XAL-compiled routing heuristics, validated against spectral gates.
3. **Proof-Term Integrity:** Every admissible action is accompanied by a **Lean 4 proof term**, verifiable by a 10MB "Pi Sheriff" kernel at the edge.

## 4. Evaluation & Benchmark Plan
Aevion will be benchmarked against the current SOTA (JEPA, Genie 3, RWML) using:
- **Physical Reasoning:** Physics-RW, IntPhys 2, MVPBench.
- **Agentic Utility:** ALFWorld, τ2 Bench.
- **Governance Metrics:** Halt lead time, false/missed halt rates, and spectral residual sensitivity.

## 5. Risks & Mitigation
- **Distribution Shift:** Addressed by structural neuroplasticity and online residual testing.
- **Koopman Mis-specification:** Addressed by dissipativity-guaranteed neural operators and conservative LMI projections.

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*Submitted for DARPA CLARA TA1 — April 2026*