🚀 EvoJAX NEAT - GPU Accelerated Version

A complete NEAT (NeuroEvolution of Augmenting Topologies) implementation with GPU acceleration using JAX and EvoJAX compatibility.

🎯 Quick Start

1. Use the complete notebook: complete_neat_training.ipynb
2. Supports: Google Colab, Kaggle, and local environments
3. GPU acceleration: Automatic T4/V100/P100 detection and optimization
4. All features included: Complete NEAT training system with visualization

🚀 Features

• ✅ Multi-platform support (Colab, Kaggle, Local)
• ✅ GPU optimization (Auto-detect and configure)
• ✅ Complete NEAT implementation (All training features)
• ✅ EvoJAX compatibility (JAX type issues resolved)
• ✅ Visualization & analysis (Training results charts)
• ✅ Auto-download (Results packaging and download)

📁 Files

• complete_neat_training.ipynb - Complete training notebook (ready to use)
• requirements.txt - Python dependencies
• setup.py - Package installation script
• neat_implementation/ - Core NEAT implementation
• evojax/ - EvoJAX framework

Ready to run on Colab/Kaggle with GPU acceleration! 🎮