About this hub

The Autophage Protocol simulations hub provides access to all simulation tools and analyses that validate the protocol's economic and biological principles. From interactive browser-based visualizations to comprehensive Python scripts, these tools enable empirical verification of theoretical predictions.

8 Interactive Simulations
10k+ Monte Carlo Runs
0.08-0.11 Target Gini Coefficient
23% Adversarial Agents Tested

Available Simulations

Choose from the following simulation types to explore different aspects of the Autophage Protocol:

Interactive Simulations Browser-Based

Real-time, browser-based simulations with adjustable parameters. Visualize how the protocol maintains economic balance through token decay and activity rewards.

  • Gini coefficient evolution over time
  • Token decay dynamics for all species
  • Monte Carlo statistical validation
  • Biological scaling law demonstrations
  • Downloadable Python scripts
Launch Interactive Simulations

Adversarial Analysis Security Testing

Comprehensive stress testing with agents designed to break the protocol. Demonstrates robustness against Sybil attacks, collusion, and wealth concentration attempts.

  • 8 distinct attack strategies
  • Sybil attack resistance testing
  • Collusion pool analysis
  • Whale behavior simulations
  • System resilience metrics
View Adversarial Testing

Python Script Analysis Source Code

Detailed walkthrough of the Python simulation that produced the litepaper's results. Includes complete source code with line-by-line explanations.

  • Full simulation source code
  • Implementation details
  • Parameter configurations
  • Reproducible results
  • Extension possibilities
Explore Python Implementation

Economic Simulations Revenue Model

Interactive economic model validating revenue streams and unit economics. Demonstrates path to profitability and sustainable growth.

  • Revenue stream calculator
  • Break-even analysis
  • Growth projections
  • Sensitivity analysis
  • Unit economics validation
Launch Economic Simulations

Gas Optimization Efficiency Testing

Demonstrates gas optimization strategies achieving 17,000 gas savings per unused day through lazy decay and 75% reduction via batching.

  • Lazy decay benchmarking
  • Batch processing analysis
  • State channel efficiency
  • Combined optimization impact
  • Smart contract examples
Explore Gas Optimizations

Smart Contracts Technical Reference

Comprehensive guide to the Autophage Protocol smart contracts, including implementation details, security considerations, and deployment strategies.

  • Contract architecture overview
  • Core interfaces and implementations
  • Security audit recommendations
  • Gas optimization techniques
  • Integration examples
View Smart Contracts Guide

Key Simulation Findings

Convergence Properties

Across all simulations, the Autophage Protocol demonstrates consistent convergence to equitable wealth distribution:

Technical Implementation

All simulations share common technical foundations while exploring different aspects of the protocol:

Browser-Based Simulations

Built with Chart.js for visualization and vanilla JavaScript for computation. Real-time parameter adjustment allows exploration of edge cases. Simulations run entirely client-side for privacy and performance.

Python Simulations

Implemented using NumPy for numerical computation, Matplotlib for visualization, and standard libraries for statistical analysis. Monte Carlo methods ensure robustness across parameter ranges. Agent-based modeling captures emergent behaviors.

Validation Methodology

Each simulation type validates different protocol aspects: economic convergence through Gini coefficient tracking, system stability via stress testing, and theoretical predictions through statistical analysis. Results are cross-validated between implementation approaches.

Additional Resources

For researchers and developers interested in extending these simulations:

"The best way to understand a complex system is to simulate it under adversarial conditions."