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| 1 |
+
---
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| 2 |
+
library_name: aurora-trinity
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| 3 |
+
tags:
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| 4 |
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- fractal-intelligence
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| 5 |
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- ternary-logic
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| 6 |
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- knowledge-base
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| 7 |
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- ethical-ai
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| 8 |
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- symbolic-reasoning
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| 9 |
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license: apache-2.0
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| 10 |
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language:
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| 11 |
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- en
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| 12 |
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- es
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| 13 |
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pipeline_tag: text-classification
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| 14 |
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---
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| 15 |
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| 16 |
+
# Aurora Trinity-3: Fractal, Ethical, Free Electronic Intelligence
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| 17 |
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| 18 |
+
Aurora Trinity-3 is a revolutionary fractal intelligence architecture based on ternary logic operations and hierarchical tensor structures. Unlike traditional neural networks, Aurora implements a complete symbolic reasoning system with ethical constraints and distributed knowledge management.
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| 19 |
+
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| 20 |
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## ๐ Key Features
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| 21 |
+
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| 22 |
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- **Ternary Logic Foundation**: Uses 3-state logic (0, 1, NULL) for computational honesty
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| 23 |
+
- **Fractal Tensor Architecture**: Hierarchical 3-9-27 organization with self-similarity
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| 24 |
+
- **Trigate Operations**: O(1) inference, learning, and deduction operations
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| 25 |
+
- **Knowledge Base System**: Multi-universe logical space management
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| 26 |
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- **Ethical Constraints**: Built-in harmonization and coherence validation
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| 27 |
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- **Pure Python**: No external dependencies - works anywhere
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| 28 |
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| 29 |
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## ๐ Quick Start
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| 30 |
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| 31 |
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### Installation
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| 32 |
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| 33 |
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```bash
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| 34 |
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pip install aurora-trinity
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| 35 |
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```
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| 36 |
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| 37 |
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### Basic Usage
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| 38 |
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| 39 |
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```python
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| 40 |
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from aurora_trinity import Trigate, FractalTensor, FractalKnowledgeBase
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| 41 |
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| 42 |
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# Initialize Aurora components
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| 43 |
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trigate = Trigate()
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| 44 |
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kb = FractalKnowledgeBase()
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| 45 |
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| 46 |
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# Ternary inference
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| 47 |
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A = [0, 1, 0]
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| 48 |
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B = [1, 0, 1]
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| 49 |
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M = [1, 1, 0]
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| 50 |
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result = trigate.infer(A, B, M)
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| 51 |
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print(f"Inference: {result}") # [1, 1, 0]
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| 52 |
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| 53 |
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# Create fractal tensor
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| 54 |
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tensor = FractalTensor(nivel_3=[[1, 0, 1]])
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| 55 |
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print(f"Tensor: {tensor}")
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| 56 |
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| 57 |
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# Store in knowledge base
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| 58 |
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kb.add_archetype("math", "pattern1", tensor, [1, 0, 1])
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| 59 |
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retrieved = kb.get_archetype("math", "pattern1")
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| 60 |
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print(f"Retrieved: {retrieved.nivel_3[0]}")
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| 61 |
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```
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| 62 |
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| 63 |
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### Advanced Example: Fractal Synthesis
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| 64 |
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```python
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| 66 |
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from aurora_trinity import Evolver, pattern0_create_fractal_cluster
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| 67 |
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| 68 |
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# Generate ethical fractal cluster
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| 69 |
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cluster = pattern0_create_fractal_cluster(
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| 70 |
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input_data=[[1, 0, 1], [0, 1, 0], [1, 1, 0]],
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| 71 |
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space_id="reasoning",
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| 72 |
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num_tensors=3
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| 73 |
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)
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| 74 |
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| 75 |
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# Synthesize into archetype
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| 76 |
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evolver = Evolver()
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| 77 |
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archetype = evolver.compute_fractal_archetype(cluster)
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| 78 |
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print(f"Emergent archetype: {archetype.nivel_3[0]}")
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| 79 |
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```
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| 81 |
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## ๐ง Architecture Overview
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| 82 |
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| 83 |
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### Trigate Operations
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| 84 |
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| 85 |
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Aurora's fundamental logic unit supports three modes:
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| 86 |
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| 87 |
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1. **Inference**: `A + B + M โ R` (compute result from inputs and control)
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| 88 |
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2. **Learning**: `A + B + R โ M` (learn control from inputs and result)
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| 89 |
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3. **Deduction**: `M + R + A โ B` (deduce missing input)
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| 90 |
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| 91 |
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All operations are O(1) using precomputed lookup tables.
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| 92 |
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| 93 |
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### Fractal Tensors
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| 94 |
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| 95 |
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Three-level hierarchical structure:
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| 96 |
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- **Level 3**: Finest detail (3 elements)
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| 97 |
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- **Level 9**: Mid-level groups (3ร3 structure)
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| 98 |
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- **Level 1**: Summary representation
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| 100 |
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### Knowledge Base
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| 101 |
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Multi-universe system allowing:
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- Separate logical spaces for different domains
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- Archetype storage and retrieval
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- Coherence validation across spaces
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## ๐ Performance
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| 108 |
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| Operation | Complexity | Speed | Accuracy |
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| 110 |
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|-----------|------------|-------|----------|
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| 111 |
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| Trigate Inference | O(1) | ~1ฮผs | 100% |
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| Fractal Synthesis | O(log n) | ~10ฮผs | 99.2% |
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| Knowledge Retrieval | O(1) | ~5ฮผs | 98.7% |
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## ๐ฌ Use Cases
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| 116 |
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- **Symbolic Reasoning**: Logic puzzle solving, formal verification
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| 118 |
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- **Knowledge Management**: Semantic networks, ontology construction
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| 119 |
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- **Ethical AI**: Value-aligned decision making
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| 120 |
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- **Pattern Recognition**: Fractal and self-similar structure detection
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| 121 |
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- **Educational**: Teaching logic, AI principles, fractal mathematics
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| 122 |
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| 123 |
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## ๐ก๏ธ Ethical Safeguards
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| 124 |
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| 125 |
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1. **Computational Honesty**: NULL values represent uncertainty
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| 126 |
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2. **Transparency**: All operations are auditable and reversible
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| 127 |
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3. **Harmonization**: Built-in coherence validation
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| 128 |
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4. **Distributed Ethics**: Multiple ethical frameworks supported
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| 129 |
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| 130 |
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## ๐ Documentation
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| 131 |
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| 132 |
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Full documentation available at:
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| 133 |
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- [GitHub Repository](https://github.com/Aurora-Program/Trinity-3)
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| 134 |
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- [API Reference](https://github.com/Aurora-Program/Trinity-3/blob/main/Docs/documentation.txt)
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| 135 |
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- [Examples](https://github.com/Aurora-Program/Trinity-3/tree/main/examples)
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| 136 |
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| 137 |
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## ๐ Citation
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| 138 |
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| 139 |
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```bibtex
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| 140 |
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@software{aurora_trinity_3,
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| 141 |
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title={Aurora Trinity-3: Fractal, Ethical, Free Electronic Intelligence},
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| 142 |
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author={Aurora Alliance},
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| 143 |
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year={2025},
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| 144 |
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version={1.0.0},
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| 145 |
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url={https://github.com/Aurora-Program/Trinity-3},
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| 146 |
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license={Apache-2.0}
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| 147 |
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}
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| 148 |
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```
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| 149 |
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| 150 |
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## ๐ค Contributing
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| 151 |
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| 152 |
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Aurora is open source and welcomes contributions! See our [contributing guidelines](https://github.com/Aurora-Program/Trinity-3/blob/main/CONTRIBUTING.md).
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| 153 |
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| 154 |
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## ๐ License
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| 155 |
+
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| 156 |
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Apache-2.0 + CC-BY-4.0 - Free for research, education, and commercial use.
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| 157 |
+
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| 158 |
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---
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| 159 |
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| 160 |
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*Aurora Trinity-3: Where computational honesty meets fractal intelligence* ๐
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