DOI: 10.5281/zenodo.18649656
title: S³–CORE™ v4: Runtime Simulation & Sovereign AI Command Governance Pilot Demonstrator Pack Version 4 — Simulation Evidence (Procurement-Discussable)

description:  



S³–CORE™ v4: Runtime Simulation & Sovereign AI Command Governance Pilot Demonstrator Pack

Version 4 — Simulation Evidence (Procurement-Discussable)

This repository contains the Version-4 Runtime Simulation release of theS³–CORE™ (Sovereign System of Structured Command, Oversight, Recurrence & Execution) framework, developed as a procurement-evaluable pilot demonstrator architecture for sovereign execution governance in AI-mediated command environments.

Version-4 delivers an implementation-aligned Simulation Evidence Pack designed to support pilot-track technical evaluation across mission-critical decision infrastructures including civil command systems, defence execution chains, intelligence coordination environments, and regulatory automation frameworks operating under mandate-bound authority structures.

The v4 demonstrator operationalizes sovereign decision execution logic through mathematically instantiated runtime control models and corresponding Python-based simulation engines. These modules enable demonstrable validation of:



Decision Object (DO) authorization eligibility

Jurisdiction-bound execution gating

Human-attributable accountability mapping

Review-Controlled Legal Eligibility (RCLE) mandate lifecycle

Attribution-Enabled Policy Logging (AEPL) audit capture

Execution traceability across runtime command pathways

Machine-verifiable legal compliance certification


All simulated execution requests are processed through runtime-validated Decision Objects via the DO–RE Execution Engine, ensuring that no AI-mediated or delegated system action occurs outside legally attributable mandate conditions.

Execution eligibility is continuously governed by the Recurring Control Loop Engine (RCLE), under which all command pathways are review-bound, renewal-dependent, and sunset-triggerable in accordance with temporal legal continuity requirements.

The AEPL Audit Logging Engine records attribution-linked execution traces for simulated ISR command scenarios, enabling theatre-level audit reconstruction, decision authority mapping, and override-state capture under runtime simulation conditions.

The v4 release is structured as a Seven-Document Runtime Simulation Pack intended for procurement-track demonstrator assessment:




PDF
Module Title
Procurement Function




PDF-1
Runtime Architecture Specification
System Overview


PDF-2
DO–RE Python Simulation Module
Execution Gate


PDF-3
RCLE Timer Engine Simulation
Mandate Expiry


PDF-4
AEPL Audit Log Engine
ROE Attribution


PDF-5
Execution Audit Trail Output
Human Accountability


PDF-6
Machine Compliance Certificate Engine
Legal Output


PDF-7
ISR Pilot Scenario Simulation
End-to-End Demonstrator




Each module contains formally defined LaTeX-based runtime logic specifications alongside executable Python simulation components representing decision authorization, jurisdictional validation, temporal mandate enforcement, attribution-linked execution logging, audit-traceable runtime activity, and compliance certification issuance under simulated operational constraints.

The ISR Pilot Scenario Simulation integrates Decision Object validation, Runtime Execution gating, RCLE mandate lifecycle control, AEPL attribution verification, and Machine Compliance Certification to demonstrate end-to-end execution eligibility across simulated command-authority scenarios.

S³–CORE™ v4 is released as a Restricted-access Dataset for Commercial Evaluation under procurement-track pilot demonstrator conditions. This version provides implementation-aligned simulation evidence for runtime governance validation, technical compliance review, and sovereign command-system pilot feasibility analysis in AI-enabled execution infrastructures.

All rights reserved. Commercial licensing applicable.