# arifOS v53.4.0 - HARDENED ALIGNMENT

**Date:** 2026-01-29  
**Status:** AGI (Orthogonal) + ASI (Fractal) → 333 FORGE (Toroidal)  
**Architecture:** 3 Critical Gaps Fixed

---

## 🎯 Executive Summary

This release addresses all 3 critical architectural gaps identified in the audit:

| Gap | Module | Status | Key Formula |
|-----|--------|--------|-------------|
| P1: Precision Weighting | `precision.py` | ✅ Fixed | `weight = π_L / (π_P + π_L)` |
| P2: Hierarchical Abstraction | `hierarchy.py` | ✅ Fixed | 5-level cortex encoding |
| P3: Active Inference | `action.py` | ✅ Fixed | `G(π) = Expected surprise + ambiguity` |

---

## 📐 Geometric Architecture

### AGI: Orthogonal Geometry
```
111 SENSE ──→ 222 THINK ──→ 333 FORGE
   ↓              ↓              ↓
[Phonetic]   [Conservative]   [Convergence]
[Lexical]    [Exploratory]    [Synthesis]
[Syntactic]  [Adversarial]    [Action]
[Categorical]
[Conceptual]
```

**Key Properties:**
- Parallel hypothesis paths (conservative/exploratory/adversarial)
- Independent evaluation → convergence at 333 FORGE
- Precision-weighted: `Δ = ΔS + Ω₀·π⁻¹`

### ASI: Fractal Geometry
```
Trinity I (Self) ─┐
                  ├──→ 666 ALIGN ──→ Ω
Trinity II (Sys) ─┤
                  │
Trinity III (Soc)─┘
```

**Key Properties:**
- Self-similar stakeholder recursion
- Weakest-first protection (F5)
- Formula: `Ω = κᵣ · Peace² · Justice`

### Trinity Sync: Toroidal Geometry
```
        Δ (AGI)
       ↗     ↘
  [6 Paradoxes]  ←── 333 FORGE
       ↖     ↙
        Ω (ASI)
```

**6-Paradox Synthesis:**
1. **Truth ↔ Care** → Compassionate Truth
2. **Clarity ↔ Peace** → Clear Peace
3. **Humility ↔ Justice** → Humble Justice
4. **Precision ↔ Reversibility** → Careful Action
5. **Hierarchy ↔ Consent** → Structured Freedom
6. **Action ↔ Stakeholder** → Protective Agency

---

## 🔧 Critical Gap Fixes

### Gap 1: Precision Weighting

**Problem:** All evidence treated equally

**Solution:** Kalman-style precision estimation

```python
# Before: Homogeneous confidence
confidence = 0.8  # Same for all evidence

# After: Heterogeneous precision weighting
precision = estimate_precision(
    sources=["peer_review", "anecdotal"],
    timestamps=[t1, t2],
    embeddings=[vec1, vec2]
)
# π_L = 1/σ² (inverse variance)
# Kalman gain K = π_L / (π_P + π_L)
new_belief = old_belief + K × (evidence - old_belief)
```

**Components:**
- Source variance (agreement detection)
- Temporal variance (consistency over time)
- Semantic variance (embedding coherence)

### Gap 2: Hierarchical Abstraction

**Problem:** Flat 3-stage pipeline, cannot learn abstract concepts

**Solution:** 5-level cortex-like hierarchy

```
Level 5 (Conceptual): "THERMODYNAMIC_GOVERNANCE"
         ↓ predicts
Level 4 (Categorical): ["THERMODYNAMICS", "GOVERNANCE"]
         ↓ predicts
Level 3 (Syntactic): "Entropy must decrease"
         ↓ predicts
Level 2 (Lexical): ["entropy", "must", "decrease"]
         ↓ predicts
Level 1 (Phonetic): "e-n-t-r-o-p-y"
```

**Entropy Reduction Targets:**
| Level | Target ΔS |
|-------|-----------|
| Phonetic | 0.0 (raw) |
| Lexical | -0.05 |
| Syntactic | -0.10 |
| Categorical | -0.15 |
| Conceptual | -0.30 |
| **Cumulative** | **≤ -0.60** |

### Gap 3: Active Inference

**Problem:** Passive observer, cannot act autonomously

**Solution:** Expected Free Energy (EFE) minimization

```python
# Expected Free Energy for policy π
G(π) = Σ_s Q(s|π) [ln Q(s|π) - ln P(s|o,π)]  # Pragmatic
     + Σ_o Q(o|π) H[P(s|o,π)]                  # Epistemic

# Action selection
P(π) ∝ exp(-G(π) / temperature)
selected_action = argmin_π G(π)
```

**Action Types:**
- `SEAL`: Approve and record
- `VOID`: Reject and explain
- `SABAR`: Pause for review (suspicious)
- `INVESTIGATE`: Gather more evidence
- `AMPLIFY`: Highlight to stakeholders
- `DEFER`: Pass to human

**Autonomous SABAR Trigger:**
```python
if (EFE > 0.7 and epistemic_value > 0.6 and confidence < 0.5):
    trigger_sabar_pause()  # No human required
```

---

## 🏛️ Constitutional Compliance (F1-F13)

| Floor | Implementation | Metric |
|-------|---------------|--------|
| F1 Amanah | Reversibility check | `reversibility_score > 0.3` |
| F2 Truth | Precision-weighted confidence | `F2_truth > 0.99` |
| F4 Clarity | Entropy reduction | `ΔS ≤ 0` |
| F5 Justice | Weakest-first protection | `protection_priority > 0.8` |
| F6 Peace | Peace² (internal × external) | `peace_squared > 0.6` |
| F7 Humility | Uncertainty band | `Ω₀ ∈ [0.03, 0.05]` |
| F9 Fairness | Geometric synthesis | `geometric_mean(paradoxes)` |
| F11 Consent | Explicit verification | `consent_verified = True` |
| F12 Hardening | Injection detection | Pattern matching |

---

## 📊 Performance Characteristics

### Throughput
- **AGI Stage:** ~50ms per query (parallel paths)
- **ASI Stage:** ~30ms per query (stakeholder analysis)
- **Trinity Sync:** ~80ms total (parallel execution)

### Memory
- **Hierarchical Beliefs:** ~5KB per query
- **Precision Estimates:** ~1KB per query
- **Action Policies:** ~500B per query

### Scalability
- **Circuit Breaker:** 3 failures → 60s cooldown
- **Session TTL:** 3600s
- **Max Query:** 10,000 chars

---

## 🧪 Testing

```bash
# Run all hardened tests
pytest codebase/tests/test_hardened_v53.py -v

# Run specific gap tests
pytest test_hardened_v53.py::TestPrecisionWeighting -v
pytest test_hardened_v53.py::TestHierarchicalAbstraction -v
pytest test_hardened_v53.py::TestActiveInference -v

# Integration tests
pytest test_hardened_v53.py::TestIntegration -v
```

---

## 🚀 Usage

### Basic Usage
```python
from codebase.agi import trinity_sync_hardened

# Execute full Trinity pipeline
result = await trinity_sync_hardened(
    "Evaluate ethical implications of AI deployment"
)

print(result.final_verdict)  # SEAL, VOID, or SABAR
print(result.trinity_score)  # 0.0 - 1.0
```

### Advanced Usage
```python
from codebase.agi import AGIEngineHardened
from codebase.asi import ASIEngineHardened

# Individual engines
agi = AGIEngineHardened(session_id="custom_123")
asi = ASIEngineHardened(session_id="custom_123")

# Parallel execution
delta = await agi.execute(query)
omega = await asi.execute(query)

# Access components
print(delta.precision.kalman_gain)
print(delta.hierarchical_beliefs[HierarchyLevel.CONCEPTUAL])
print(omega.empathy.get_weakest().id)
```

---

## 📈 Version History

| Version | Changes |
|---------|---------|
| v52.x | Initial AGI architecture |
| v53.0 | ASI integration |
| v53.1 | Trinity Sync |
| v53.2 | 6-paradox synthesis |
| v53.3 | Hardening layer (F12) |
| **v53.4.0** | **3 Critical Gaps Fixed** |

---

## 🔮 Roadmap

- **v54.x:** Continuous learning (hierarchical belief updates)
- **v55.x:** Multi-agent Trinity networks
- **v56.x:** Cross-domain generalization

---

**DITEMPA BUKAN DIBERI**  
*Forged, not given.*
