AETRE & The Governed Agent

AETRE & The Governed Agent: Unified Decision-Theoretic Operating System

"Governing Autonomous Intelligence in the Age of Abundance."

A high-performance, mathematically unified decision-theoretic operating system uniting macroeconomic proposal/portfolio triage (AETRE) and microeconomic execution governance (The Governed Agent).

Release status: experimental public alpha. The software and mathematical

simulations are testable, but the demonstration records are synthetic and do not

establish prospective effectiveness in a live conference, grant, or

investment workflow. Use outputs as decision-support diagnostics, not as

autonomous acceptance, rejection, funding, or investment decisions.

Based on the research series by Clayton Gray (2026):

1. The Innovation-Absorption Gap: How Artificial Intelligence Can Accelerate Idea Production Faster Than Complementary Institutions Adapt *Clayton Gray (2026a)* — SSRN: 7161458
2. The Admission Frontier: An Economically Regulated Decision-Theoretic Runtime and Fail-Closed Verification Gate for Autonomous Agents *Clayton Gray (2026d)* — distributed within the replication bundle *The Implementation Frontier: Capital Allocation, Deliberative Stopping, and Verified Agent Gatekeeping* (Zenodo: 10.5281/zenodo.22814799)

This software is archived under its own DOI, separate from the papers above: AETRE: Adaptive Epistemic Triage & Recall Engine (Zenodo: 10.5281/zenodo.22098366).

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The Problem: The Innovation-Absorption Gap

When Artificial Intelligence makes idea and action generation cheap ($c_{\text{gen}} \to 0$), proposal and execution volume ($N$) explodes. However, downstream evaluation, laboratory validation, code review, and human gatekeeper capacity ($K$) remain strictly finite.

This creates three critical pipeline pathologies:

1. The Kingman Delay Explosion: When evaluator utilization $\rho = \lambda / \mu$ approaches saturation ($\rho > 0.85$), wait times shoot up non-linearly according to Kingman's Heavy-Traffic equation: $$E[W_q] \approx \frac{\rho}{1-\rho} \cdot \frac{c_a^2 + c_s^2}{2} \cdot \frac{1}{\mu}$$
2. The Asymmetric Payoff Trap: In heavy-tailed domains like venture capital, breakthrough discovery, and agentic code patches (Pareto index $\alpha \approx 1.25$), consensus-seeking scoring systems penalize high-variance, transformative outliers in favor of safe, incremental proposals.
3. The Finite-Capacity Recall Ceiling (Proposition 1): Without active epistemic triage, true breakthrough recall asymptotically decays towards zero as arrival rates surge: $$R_N \le \min\left(1, \frac{K_N}{H_N}\right) \to 0 \quad \text{as } N \to \infty$$

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Two-Layer Decision-Theoretic Architecture

AETRE unifies Macroeconomic Pipeline Triage (managing institutional review bandwidth and portfolio recall) with Microeconomic Execution Governance (safeguarding agentic execution runtimes and pull-request verification).

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MACRO LEVEL: Institutional Proposal & Portfolio Triage (AETRE / Gray 2026a) ======================================================================================== Incoming Submissions / Dealflow (N) │ ▼ ┌─────────────────────────────────────────────────────────┐ │ 1. Bayesian Value-of-Information (VOI) Engine │ │ - Closed-form normal VOI & Pareto heavy-tailed VOI │ │ - Direct-Pass, Fast-Drop, or Deep-Review allocation │ └─────────────────────────────────────────────────────────┘ │ ▼ ┌─────────────────────────────────────────────────────────┐ │ 2. Kingman Heavy-Traffic Capacity Governor │ │ - Dynamic queue throttling when ρ → 1.0 │ │ - Preserves reviewer quality; deters burnout │ └─────────────────────────────────────────────────────────┘ │ │ ▼ ▼ [ Admitted Cohort (K) ] [ Exploration Audit Pool ] Optimal Conviction Allocation Horvitz-Thompson H_hat_D Unbiased Audit

======================================================================================== MICRO LEVEL: Autonomous Execution & Verification Gate (Governed Agent / Gray 2026d) ======================================================================================== Autonomous PRs / Candidate Actions │ ▼ ┌─────────────────────────────────────────────────────────┐ │ 3. Tripartite Review Boundary & Bellman DP (Road A) │ │ - Computes Expected Value of Verification (V*) │ │ - Classifies AUTO_EXECUTE, REQUIRE_REVIEW, or REJECT │ │ - Fail-Closed: Rejects on malformed input/divergence │ └─────────────────────────────────────────────────────────┘ │ ▼ ┌─────────────────────────────────────────────────────────┐ │ 4. Heterogeneous cμ-Rule Knapsack Controller │ │ - Value density sorting: ρ_i = Δu_i / c_i │ │ - Budget-constrained admission under shadow prices │ └─────────────────────────────────────────────────────────┘ │ │ ▼ ▼ [ Auto-Merged / Dispatched ] [ Escalated to Human Gatekeeper ]

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Repository Structure

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├── Cargo.toml # Workspace manifest (AGPL-3.0) ├── crates/ │ ├── aetre-core/ # Pure Rust decision engine: │ │ ├── src/voi.rs # - Bayesian VOI & heavy-tailed Pareto │ │ ├── src/governor.rs # - Bellman DP & Tripartite Review Boundary (Road A) │ │ ├── src/knapsack.rs # - Heterogeneous cμ-rule knapsack controller │ │ ├── src/queues.rs # - Kingman heavy-traffic capacity governor │ │ ├── src/audit.rs # - Horvitz-Thompson exploration audit │ │ └── src/staking.rs # - Super-linear anti-sybil staking │ ├── aetre-cli/ # Native CLI for simulations, bounds & backtests │ └── aetre-mcp/ # Model Context Protocol server (24 tools, 4 resources, 3 prompts) ├── python/ │ └── governed_agent/ # Python reference runtime for agent execution governance ├── scripts/ │ └── pre-commit-governed-gate.py # Standalone pre-commit verification gatekeeper ├── tests/ # Python unit & regression suite (79 tests) ├── benchmarks/ # Verification benchmarks and institutional queue sweeps ├── examples/ │ ├── datasets/ # Held-out review and dealflow test splits │ ├── proposals.json # Benchmark evaluation candidates │ └── mcp_config.json # Claude Desktop & Cursor connection template ├── .pre-commit-hooks.yaml # Pre-commit hook definition for git integration ├── .github/workflows/ │ ├── ci.yml # Rust & MCP server automated verification │ └── governed-gate-template.yml # Reusable GitHub Actions agent PR gating workflow ├── CITATION.cff # Dual academic citation metadata ├── Dockerfile # Production container definition ├── fly.toml # Serverless Cloud deployment config ├── DATASETS.md # Fixture provenance and third-party data guidance ├── LICENSE # GNU Affero General Public License v3.0 text ├── LICENSING.md # AGPL licensing and publication status └── README.md

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Quickstart & CLI Usage

1. Run the Rust Test Suite & Verification

cargo test --workspace

cargo clippy --workspace --all-targets -- -D warnings

2. Run the Python Reference Governance Suite

python -m unittest discover -s tests

3. Run the Standalone Governed Agent Pre-Commit Gate

Fast, fail-closed verification gate for agentic code modifications:

python scripts/pre-commit-governed-gate.py --all-files

4. Run the Macro Monte Carlo & Dealflow Benchmarks

# Multi-regime academic triage simulation (500 replications)

cargo run -p aetre-cli -- benchmark --replications 500

Venture Capital Pareto dealflow benchmark (10,000 deals, α = 1.25)

cargo run -p aetre-cli -- vc-benchmark --deals 10000 --budget 100 --alpha 1.25

Theoretical Proposition 1 recall ceiling bound

cargo run -p aetre-cli -- bound --arrivals 5000 --capacity 200 --high-rate 0.067 --csv

5. Simulate Institutional Heterogeneous Agent Queues

Simulates density-greedy $c\mu$-rule knapsack vs. FIFO across varying institutional review capacities:

python evaluate_institutional_queues.py

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Model Context Protocol (MCP) Integration

AETRE provides a high-performance native JSON-RPC 2.0 Model Context Protocol (MCP) server implementing 24 Tools, 4 Resources, and 3 Pre-Configured Prompts for Claude Desktop, Cursor, and autonomous agent sidecars.

Configuration (Claude Desktop / Cursor)

Install the binary (cargo install aetre-mcp), then add to your claude_desktop_config.json. The server speaks stdio by default:

{

"mcpServers": { "aetre": { "command": "aetre-mcp" } } }

Local HTTP / Container Mode

cargo run -p aetre-mcp -- --serve --headless

HTTP mode binds to 127.0.0.1:8080 by default and does not enable cross-origin browser access. For container deployment, set AETRE_BIND_ADDRESS=0.0.0.0 and set a strong AETRE_HTTP_SERVER_TOKEN. Non-loopback startup fails closed when that token is absent. POST clients must send it in the X-AETRE-Server-Token header. Also place the service behind a TLS reverse proxy. The bundled Dockerfile supplies the bind address and runs as a non-root user.

Comprehensive 24-Tool Catalog

Macroeconomic Pipeline & Portfolio Tools (AETRE)

1. aetre_system_catalog: Diagnostic catalog of registered tools, resources, and algorithms.
2. aetre_triage_proposal: Full three-stream triage routing (FAST_DROP, VOI_QUEUE, AUTO_PASS).
3. aetre_calculate_voi: Closed-form Gaussian Value-of-Information ($V^*$) calculation.
4. aetre_check_governor: Kingman heavy-traffic queue delay ($E[W_q]$) forecasting and capacity throttling.
5. aetre_exploration_audit: Horvitz-Thompson unbiased discovery rate estimator ($\hat{H}_D$) for rejected pools.
6. aetre_evaluate_staking: Anti-sybil quadratic staking schedule for incoming proposals.
7. aetre_proposition_1_bound: Asymptotic recall bound ($R_N \le \min(1, K_N / H_N)$) verification.
8. aetre_correlated_posterior_update: Multi-agent reviewer consensus correlation debiasing.
9. aetre_heavy_tailed_voi: Pareto power-law ($\alpha \approx 1.25$) expected value of information for extreme outcomes.
10. `aetr