ECONGAMES: Monte-Carlo Game-Theory Toolkit
Overview
Build a professional-grade Monte Carlo simulation toolkit for analyzing game-theoretic scenarios in economics. Implement strategies like Tit-for-Tat and Grim Trigger for repeated games such as the Prisoner’s Dilemma.
What You’ll Build
A pip-installable Python package with CLI that:
- Simulates repeated 2-player normal-form games
- Implements multiple classic strategies
- Performs statistical analysis of outcomes
- Provides insights into cooperation vs. competition dynamics
Key Skills Developed
- Software Engineering: Strict type checking, 90% test coverage, CI/CD pipeline
- Game Theory: Nash equilibria, strategic interactions, evolutionary dynamics
- Statistics: Hypothesis testing, Monte Carlo methods, convergence analysis
- Professional Tools: MyPy, Ruff, pytest, pre-commit hooks, GitHub Actions
Why This Project?
Game theory underlies many economic phenomena from price wars to environmental cooperation. This project gives you hands-on experience building research-grade simulation tools while enforcing professional software engineering standards.
Difficulty Level
⭐⭐⭐⭐⭐ Advanced
This is one of the most challenging projects, requiring:
- Strong Python skills
- Mathematical understanding
- Rigorous testing discipline
- Statistical analysis capabilities
Getting Started
- Use the template repository to create your own project
- Review the comprehensive project brief for detailed requirements
- Set up your development environment with
make install-dev - Start with the Week 2 milestone: Random vs Random simulation
Ready to master game theory through code? This project will push your software engineering skills to professional standards.