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 bundled data 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):
- The Innovation-Absorption Gap: How Artificial Intelligence Can Accelerate Idea Production Faster Than Complementary Institutions Adapt
Clayton Gray (2026a) β SSRN: 7161458
- The Admission Frontier: An Economically Regulated Decision-Theoretic Runtime and Fail-Closed Verification Gate for Autonomous Agents
Clayton Gray (2026d) β 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).
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:
- 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:
$$E[W_q] \approx \frac{\rho}{1-\rho} \cdot \frac{c_a^2 + c_s^2}{2} \cdot \frac{1}{\mu}$$
- 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.
- The Finite-Capacity Recall Ceiling (Proposition 1): Without active epistemic triage, true breakthrough recall asymptotically decays towards zero as arrival rates surge:
$$R_N \le \min\left(1, \frac{K_N}{H_N}\right) \to 0 \quad \text{as } N \to \infty$$
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)
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Incoming Submissions / Dealflow (N)
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β 1. Bayesian Value-of-Information (VOI) Engine β
β - Closed-form normal VOI & Pareto heavy-tailed VOI β
β - Direct-Pass, Fast-Drop, or Deep-Review allocation β
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β 2. Kingman Heavy-Traffic Capacity Governor β
β - Dynamic queue throttling when Ο β 1.0 β
β - Preserves reviewer quality; deters burnout β
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[ Admitted Cohort (K) ] [ Exploration Audit Pool ]
Optimal Conviction Allocation Horvitz-Thompson H_hat_D Unbiased Audit
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MICRO LEVEL: Autonomous Execution & Verification Gate (Governed Agent / Gray 2026d)
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Autonomous PRs / Candidate Actions
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β 3. Tripartite Review Boundary & Bellman DP (Road A) β
β - Computes Expected Value of Verification (V*) β
β - Classifies AUTO_EXECUTE, REQUIRE_REVIEW, or REJECT β
β - Fail-Closed: Rejects on malformed input/divergence β
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β 4. Heterogeneous cΞΌ-Rule Knapsack Controller β
β - Value density sorting: Ο_i = Ξu_i / c_i β
β - Budget-constrained admission under shadow prices β
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[ Auto-Merged / Dispatched ] [ Escalated to Human Gatekeeper ]
Repository Structure
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βββ Cargo.toml # Workspace manifest (AGPL-3.0)
βββ crates/
β βββ aetre-core/ # Pure Rust decision engine:
β β βββ src/voi.rs # - Bayesian VOI & heavy-tailed Pareto
β β βββ src/governor.rs # - Bellman DP & Tripartite Review Boundary (Road A)
β β βββ src/knapsack.rs # - Heterogeneous cΞΌ-rule knapsack controller
β β βββ src/queues.rs # - Kingman heavy-traffic capacity governor
β β βββ src/audit.rs # - Horvitz-Thompson exploration audit
β β βββ src/staking.rs # - Super-linear anti-sybil staking
β βββ aetre-cli/ # Native CLI for simulations, bounds & backtests
β βββ aetre-mcp/ # Model Context Protocol server (24 tools, 4 resources, 3 prompts)
βββ python/
β βββ governed_agent/ # Python reference runtime for agent execution governance
βββ scripts/
β βββ pre-commit-governed-gate.py # Standalone pre-commit verification gatekeeper
βββ tests/ # Python unit & regression suite (79 tests)
βββ benchmarks/ # Verification benchmarks and institutional queue sweeps
βββ examples/
β βββ datasets/ # Held-out review and dealflow test splits
β βββ proposals.json # Benchmark evaluation candidates
β βββ mcp_config.json # Claude Desktop & Cursor connection template
βββ .pre-commit-hooks.yaml # Pre-commit hook definition for git integration
βββ .github/workflows/
β βββ ci.yml # Rust & MCP server automated verification
β βββ governed-gate-template.yml # Reusable GitHub Actions agent PR gating workflow
βββ CITATION.cff # Dual academic citation metadata
βββ Dockerfile # Production container definition
βββ fly.toml # Serverless Cloud deployment config
βββ DATASETS.md # Fixture provenance and third-party data guidance
βββ LICENSE # GNU Affero General Public License v3.0 text
βββ LICENSING.md # AGPL/commercial licensing overview
βββ README.md
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, Ξ± = 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