https://github.com/datacte/self-referential-neural-network
https://github.com/datacte/self-referential-neural-network
Last synced: over 1 year ago
JSON representation
- Host: GitHub
- URL: https://github.com/datacte/self-referential-neural-network
- Owner: DataCTE
- License: apache-2.0
- Created: 2024-11-21T13:48:49.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2024-11-21T15:33:11.000Z (over 1 year ago)
- Last Synced: 2025-02-05T23:42:50.630Z (over 1 year ago)
- Language: Python
- Size: 22.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Self-Referential Neural Network: CTMU Computational Framework
**warning:** this is a work in progress and not all components are fully implemented.
A Python implementation of Chris Langan's Cognitive-Theoretic Model of the Universe (CTMU), emphasizing self-referential systems, telesis, and conspansive evolution.
## Overview
This framework operationalizes core CTMU principles:
1. **Telesis**: Self-configuring causation via telic recursion
2. **Conspansive Evolution**: Reality's simultaneous expansion and contraction
3. **Unbound Telesis (UBT)**: Quantum aspects of reality formation
4. **Metaformal System**: Foundational linguistic framework
```
Self-Referential-Neural-Network/
├── ctmu_core/
│ ├── init.py
│ ├── domains/
│ │ ├── reality.py # Top-level reality implementation
│ │ └── nonterminal.py # Pre-physical domain implementation
│ ├── manifold.py # Conspansive manifold implementation
│ ├── telesis.py # Telesis (causation) implementation
│ ├── metaformal.py # Metaformal system implementation
│ ├── tellers.py # Syntactic operators
│ ├── state.py # State management
│ └── ubt.py # Unbound Telesis implementation
├── ctmu_ml/ # Machine Learning Framework
│ ├── init.py
│ ├── network.py # Self-referential neural network
│ ├── layers.py # Telic neural layers
│ └── optimizers.py # Telic optimization
└── README.md
```
## Core Components
### 1. Conspansive Manifold (`manifold.py`)
- **Key Features**:
- Quantum state evolution through UBT
- Field evolution and coherence tracking
- Distributed endomorphic connections
- Syndiffeonesis implementation
### 2. Telesis System (`telesis.py`)
- **Implements**:
- Telic recursion processing
- State combination mechanics
- Utility evaluation
- Metaformal system integration
### 3. State Management (`state.py`)
- **Components**:
- `TelicState`: Models potential-actuality dynamics
- Evolution mechanics and coherence tracking
- Utility calculation
### 4. Unbound Telesis (`ubt.py`)
- **Features**:
- Quantum collapse mechanics
- Morphic transformations
- Constraint application
- Dimensional translation
### 5. Reality Domain (`domains/reality.py`)
- **Implements**:
- `TelosVector` evolution
- Inner expansion mechanics
- Semantic-syntactic integration
- Field absorption dynamics
## Installation
Clone the repository and install the required dependencies:
```bash
git clone https://github.com/yourusername/self-referential-neural-network.git
cd self-referential-neural-network
pip install -r requirements.txt
```
## Contributing
We welcome contributions to enhance the framework's capabilities and explore new applications of CTMU principles.
## License
Apache 2.0
## Credits
Chris Langan's Cognitive-Theoretic Model of the Universe (CTMU)