README
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# Center for Cybernomics Research (CCR)
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## 🌐 About
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The Center for Cybernomics Research (CCR) is an interdisciplinary initiative from the AF2C exploring cybernetic systems for post-capitalist economic models. We combine systems theory, decentralized governance, and computational modeling to develop frameworks for resource allocation and organizational structure modelling beyond liberal markets.
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Current Focus Areas:
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- Anarchist cybernetic systems
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- Mutual aid network simulations
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- Decentralized decision-making protocols
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- Anti-hierarchical resource management
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## 📂 Repository Structure
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```
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CCR/
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├── python/ # Python implementations
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├── papers/ # Research whitepapers (upcoming)
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├── governance/ # Decision-making protocols (upcoming)
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└── flake.nix # Nix development environment
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```
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## 🚀 Getting Started
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1. Clone repository:
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```bash
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Copy
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git clone https://github.com/your-org/CCR.git
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cd CCR
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```
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2. Enable flake :
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```bash
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bash
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Copy
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nix develop # Enter unified development environment
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```
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## 🤝 Contributing
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We welcome contributions through :
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- Code : Implement new simulation modules
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- Research : Develop theoretical frameworks
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- Design : Create visualization tools
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- Documentation : Improve technical specs
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See CONTRIBUTING.md (upcoming) for guidelines.
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## 📜 License
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upcoming
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# CCR Python Simulations
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## 🥖 Bakery
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A computational model of decentralized bread production/distribution commune (type 1) inspired by Project Cybersyn.
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Key Features
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- Decentralized Voting System with consensus-based production decisions
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- Resource Cybernetics (Real-time flour/energy tracking)
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- Variable distribution priority
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- Community Trust Metrics : Feedback-loop driven scores that influence donations
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### ⚙️ Installation
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```bash
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git clone https://github.com/your-org/CCR.git
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cd CCR/python
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# Using Nix (recommended):
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`nix develop`
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# Manual setup:
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python -m venv .venv
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source .venv/bin/activate
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pip install -r requirements.txt
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```
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### 🚦 Running the Simulation
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```bash
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python run.py
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# Expected terminal output:
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Day 0: Produced 94 loaves (Consensus: 3/4)
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Day 2: Distributed 82 loaves
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Community trust: 58.3 → 64.1
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```
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### 📁 Code Structure
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```
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python/
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├── classes.py # Core models (Bakery, Member)
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├── simulation.py # Main simulation loop
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├── run.py # Visualization script using matplotlib
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├── tests/ # Unit tests (upcoming)
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└── analysis/ # Data processing notebooks (upcoming)
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```
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### 🌱 Future Development
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-[] Add crisis scenarios (resource shortages)
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-[] Implement skill-based task allocation
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-[] Connect to real data
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-[] Develop web interface
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-[] Generalize to other type 1 communes
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### 📊 Example Output
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|Day | Bread Stock | Trust Score | Production Runs
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|----|------------|-------------|-----------------
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|0 | 94 | 50.0 | 1
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|3 | 132 | 63.4 | 2
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|7 | 87 | 71.2 | 1
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### 📝 Contributing
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1. Fork the repository
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2. Create feature branch:
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```bash
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git checkout -b feature/new-voting-system
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```
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3. Submit pull request with:
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- Code changes
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- Updated tests
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- Documentation additions
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import matplotlib.pyplot as plt
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from simulation import simulate_days
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trust, bread = simulate_days(days=30)
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trust, bread = simulate_days(days=1825)
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# Plot results
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plt.figure(figsize=(12, 4))
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for day in range(days):
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# --- Daily donations ---
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bakery.flour_stock += np.random.randint(2, 10) # ~10kg/day
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bakery.energy_stock += np.random.randint(5, 30) # ~30kWh/day
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bakery.flour_stock += np.random.randint(2, 100) # ~10kg/day
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bakery.energy_stock += np.random.randint(5, 300) # ~30kWh/day
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# --- Decentralized production decision ---
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if bakery.flour_stock < 50: # Trigger production proposal
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if bakery.flour_stock >= 50: # Trigger production proposal
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votes = [member.vote("produce_bread") for member in members]
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yes_votes = sum(1 for vote in votes if vote == "yes")
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if yes_votes / len(members) >= 1: # Consensus
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if yes_votes / len(members) >= 0.75 : # Consensus
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requested_loaves = 100
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produced = bakery.produce_bread(requested_loaves)
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print(f"Day {day}: Produced {produced} loaves")
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# --- Distribute bread ---
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daily_distribution = bakery.distribute_bread({
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"mutual_aid": 50, # 50 groups needing bread
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"mutual_aid": 50, # 50 mutual aid groups
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"individuals": 100 # 100 individuals
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})
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