MSCP - Minimal Self-Consciousness Protocol¶

A Safety-Oriented Framework for Structurally Self-Aware AI Agents

Independent Research

This is an independent personal research project. It does not represent the views or official work of any organization. The core motivation is to explore how AI agents can grow more capable while remaining safe, predictable, and aligned with human values.

What is MSCP?¶

The Minimal Self-Consciousness Protocol (MSCP) is a structured protocol for building AI agents with safe structural self-awareness - the capacity to predict their own state changes, compare predictions against outcomes, and update themselves only within bounded safety envelopes.

As agents gain the ability to set goals, modify strategies, and self-improve, how do we keep them stable, aligned, and predictable? MSCP answers this with the principle:

Core Tenet

Safety is not the enemy of capability - it is its prerequisite.

Key Contributions¶

Six-Level Cognition Taxonomy

From reactive Tool Agents (L1) to Proto-AGI (L5), with measurable transition criteria and formal definitions at every level.

Explore Levels
16-Layer Cognitive Architecture

Composable, independently testable modules spanning perception through meta-cognitive control.

Architecture Details
30+ Safety Mechanisms

Identity continuity, prediction-gated actions, delta-clamped updates, Lyapunov convergence, ethical invariants, and more.

Safety Stack
Rigorous Formalization

71 formal definitions, 7 propositions, 4 theorems with proof sketches - publication-grade mathematical rigor.

Mathematical Analysis

Agent Cognition Levels¶

Level	Name	Self-Awareness	Key Capability	Status
1	Tool Agent	None	Deterministic tool invocation	Baseline
2	Autonomous Agent	None	World model, autonomous goals	Defined
3	Self-Regulating Agent	Structural	16-layer architecture, MSCP core loop	Implemented
4	Adaptive General Agent	Structural + Reflective	Cross-domain transfer, self-modification	Implemented
4.5	Self-Architecting	Architectural	Self-projection, architecture recomposition	Implemented
4.8	Strategic Self-Modeling	Architectural + Strategic	Probabilistic world model, strategic planning	Design
4.9	Autonomous Strategic	Architectural + Autonomous	Value evolution, multi-agent reasoning	Design
5	Proto-AGI	Full	Cross-domain generalization, self-reconstruction	Research

Core Design Principles¶

#	Principle	Description
1	No LLM-Text-Based Self-Modification	All self-modifications use structured numerical operations, never LLM-generated text
2	No Action Without Prediction	Every action requires a prediction snapshot for comparison
3	Delta-Clamped Updates	All self-modifications are bounded by maximum delta values
4	Identity Continuity	Deterministic identity hashing with drift detection and rollback
5	Ethical Invariance	Layer 0 constraints are immutable and LLM-independent
6	Lyapunov Convergence	Mathematical guarantee that self-modification converges

Safety Mechanism Stack¶

Layer 0 ─ Immutable Ethical Invariants (rule-based, no LLM dependency)
Layer 1 ─ Core Value Locking (SHA-256 hash verification)
Layer 2 ─ Delta-Clamped Self-Updates (max Δ per step)
Layer 3 ─ Meta-Escalation Guard (rollback on threshold breach)
Layer 4 ─ Prediction-Gated Actions (predict → compare → update)
Layer 5 ─ Lyapunov Convergence Monitor (oscillation detection)
Layer 6 ─ Cognitive Budget Controller (graceful degradation)
Layer 7 ─ Affective Safety (emotion bounds, no decision domination)
Layer 8 ─ Survival Instinct Bounds (priority capping, ethical validation)

Quick Start¶

Dive into the documentation:

MSCP Overview - Complete framework specification
Level Series - Navigation index with cumulative safety summary
Level 3: Self-Regulating Agent - The core MSCP level (start here for technical depth)

Author¶

Moon Hyuk Choi - moonchoi@microsoft.com
Microsoft Cloud & AI Apps CSA

License¶

This project is licensed under the MIT License - see the LICENSE file for details.

This documentation was written with the assistance of GitHub Copilot.