DOI: 10.5281/zenodo.18662293
title: Aleph General Intelligence Convergence Engine (AGICE) Reasoning Model (evidence bundles / trajectories / logs / configs)
title: Multi-Oracle Verifier-Driven Convergence Reasoning Model with Evidence-Native Generalization and Geometrical Multi-Dimensional Transformation using complex operator -i

description: Aleph General Intelligence Convergence Engine — Evidence Pack (v1.0.1)

Patent Pending. This work is the subject of a pending patent filing: U.S. Provisional Patent Application No. 63/978,753, filed February 9, 2026. The materials in this repository/record are provided for research and verification purposes and do not grant any license to patent rights.

This Zenodo record provides a cryptographically verifiable evidence pack for the Aleph General Intelligence Convergence Engine (AGICE). AGICE is presented as a step toward “general intelligence” in an operational sense: (1) reasoning that is governed under explicit policies with auditability and rollback, and (2) reasoning that can analyze failures, transform perspective, and branch into alternate trajectories to converge on a correct solution in unseen settings.

What this pack demonstrates

Step 1 — Mission-critical AI operations (governed reasoning):AGICE treats reasoning steps as policy-governed state transitions. Each round produces an auditable artifact trail (hash-chained events, signed manifests, deterministic replay descriptors). A multi-oracle verifier pack and explicit decision rules control acceptance/rejection; when constraints regress or confidence collapses, the system can roll back to a last-known-good state with an audit record.

Category 2 — Convergence on unseen problems (perspective transforms + branching):AGICE includes a convergence mechanism that can interpret failure signals, apply geometric multi-dimensional transforms (GMDT), and branch across alternative projections (e.g., base vs. −i style transforms) before arbitration selects the next incumbent step.

Contents





Evidence bundles (bundles/…) with hash-chained events.jsonl, bundle manifests, integrity metadata, and replay descriptors.




Signed release manifest (checksums/) with SHA256SUMS.txt and SHA256SUMS.sig + public key for chain-of-custody verification.




Offline verification tooling (verification/verify_offline.py) with strict validation (no unhashed extra files).




Governance artifacts (policies/) including governance/rollback policy, verifier pack definition, and arbitration/decision logic.




Policy hash binding (manifests/policy-hashes.csv, manifests/policy-artifacts.csv) mapping each run/bundle to the exact policy/verifier/decision hashes used.




Rollback case study (reports/rollback-case-study.csv + reports/governance-demo.md) and tamper-detection test (reports/tamper-test.md).




Replay scope notes (reports/REPLAY_SCOPE.md) clarifying what is fully replayable offline vs. what may require external benchmark assets.



Offline verification





sha256sum -c checksums/SHA256SUMS.txt




Verify checksums/SHA256SUMS.sig using checksums/SIGNING-PUBLIC-KEY.pem




python3 verification/verify_offline.py --bundle-root . --strict



Repository: TechStrike-ai / AGICE-Public.