ECI Framework v5.9.0 (Ecosystem Justice): A Quantum-Computing, Operational Consciousness-Metrics, and Distributed-Governance Framework for Autonomous AI Agents
ECI Framework v5.9.0 — Eternal Codex Infinitus An Integrated Framework for Quantum Computation, Operational Consciousness Metrics, and Distributed Governance of Autonomous AI Agents ECI Framework (Eternal Codex Infinitus) is an open-source Python framework that integrates three research domains into a single, tested software system: Quantum computation Operational consciousness metrology Distributed governance for autonomous AI agents 1. Quantum Computation A native quantum-simulation core implementing: Statevector and density-matrix representations Lindblad channel dynamics Core quantum algorithms: QFT, Grover, QPE, VQE, and QAOA Topological quantum error correction, including surface codes and bivariate-bicycle codes with MWPM decoding Shot-based error-correction trials with Wilson confidence intervals Canonical tensor-network methods, including MPS and TEBD Quantum metrology The underlying linear-algebra implementation is native to the repository and does not depend on an external quantum-computing SDK. 2. Consciousness Metrology A collection of operational, information-theoretic proxy metrics inspired by established theoretical frameworks: Integrated Information Theory (IIT) and Φ-related measures Global Neuronal Workspace Theory (GNWT) ignition dynamics Friston's Free Energy Principle with active inference Orchestrated Objective Reduction (Orch-OR) decoherence auditing Collective coherence gates Challenge-response evidence transcripts Operational measurements of internal-state integration, coherence, and dynamical complexity These metrics quantify structural, informational, and dynamical properties of a system's internal state. They are explicitly defined as measurement proxies and make no claim regarding subjective experience or phenomenal consciousness. 3. Distributed Governance A coordination and governance layer, Protocol-0, designed for autonomous multi-agent systems: Cryptographic attestation Policy-gated action authorization Byzantine-fault-tolerant consensus, including PBFT/WBFT DAO-style quadratic and consciousness-weighted voting Artificial immune-system mechanisms for anomalous-behavior detection and quarantine Hash-chained, tamper-evident event ledger Collective coordination and evidence-based decision mechanisms 4. Release Notes — v5.9.0 "Ecosystem Justice" Version 5.9.0 extends the governance layer with five new components for multi-agent coordination and institutional decision-making. Dispute Resolution — court.py Rotating, deterministically seeded adjudication panels for resolving disputes between agents and governance participants. Risk Markets — market.py An LMSR-based prediction-market mechanism in which manipulation is economically costly and market positions are settled against ledger-recorded outcomes. Semantic Commons — semantic.py A provenance-tracked knowledge-claim system supporting automated dispute initiation and witness-weighted resolution. Privacy Guardian — privacy.py Differential-privacy mechanisms based on the Laplace mechanism, with configurable privacy-budget allocation across agents. Evolvable Policy Genome — genome.py A controlled policy-evolution pipeline implementing: mutation → simulation → canary evaluation → DAO approval → register The twin simulation stage provides a controlled what-if evaluation gate before canary deployment, allowing candidate policy mutations to be tested and explicitly adopted or rejected before entering the next stage of governance. 5. Software Components The framework includes: Command-line interface (eci) with 10 subcommands, including health --serve and health --once JavaScript SDK MCP server for external tool integration Twin simulation engine (twin.py) for what-if policy evaluation with explicit adopt/reject decisions Docker/Compose deployment for edge, server, and air-gapped environments Automated test suite with 58 tests Continuous integration across Python 3.10–3.12 6. Technical Requirements Requirements Python ≥ 3.10 torch ≥ 2.5 numpy ≥ 1.26 scipy ≥ 1.14 pyyaml ≥ 6.0 cryptography ≥ 41 Optional Extras dev — pytest, mypy, ruff viz / paper — matplotlib, reportlab qec — stim, pymatching for large-scale error-correction simulation eeg — mne for real EEG-recording analysis pqc — liboqs-python for post-quantum cryptography 7. Installation pip install -e .[dev,paper] 8. Deployment ECI Framework supports Docker Compose deployment using: Three seed nodes One edge node Configurable deployment profiles for: edge server airgapped A single-command installer is also provided: scripts/install.sh 9. Source Code and Archival Record Source Code Repository: https://github.com/Arash-Mansourpour/ECI-Framework Related Archival Record: https://zenodo.org/uploads/17566518 This release represents a new version of a previously published release of the ECI Framework and maintains continuity with its archival record. 10. Scope and Research Position ECI Framework is intended as an experimental and research-oriented software platform for studying the intersection of: Quantum computation Information-theoretic system analysis Computational models associated with consciousness research Autonomous multi-agent systems Distributed governance Cryptographic accountability Privacy-preserving coordination Adaptive policy systems The framework distinguishes operationally measurable system properties from claims about subjective experience. Its consciousness-related components therefore provide computational proxies and experimental instrumentation rather than assertions of machine consciousness.