mjx-project/mjx
🏗️ Frameworkmjx-project
A high-performance C++ framework designed for advanced Mahjong AI research and reinforcement learning.
Mjx is a specialized research framework that addresses the unique challenges of Mahjong, a complex game characterized by imperfect information and high-dimensional state spaces. Built primarily in C++ for maximum computational efficiency, the framework allows for rapid simulation of thousands of games per second, which is critical for training deep reinforcement learning models. It includes a comprehensive suite of tools for state observation, action space management, and rule enforcement. The project provides seamless Python integration, allowing researchers to leverage popular machine learning libraries like PyTorch or TensorFlow while maintaining the high-speed execution of the underlying C++ engine. Mjx is designed to support various research methodologies, from heuristic-based approaches to sophisticated neural network architectures, making it a versatile tool for anyone exploring the intersection of game theory and artificial intelligence.
💡Highlights
- ├─High-performance C++ core
- ├─Seamless Python bindings
- └─Optimized for RL research
🎯For
- ├─AI Researchers
- ├─Game Theory Enthusiasts
- └─Reinforcement Learning Engineers