https://github.com/dunningkrueg/chess-engine-artificial-intelligence
A cutting-edge chess engine that combines state-of-the-art AI technologies with grandmaster-level chess understanding. Powered by advanced neural networks, quantum-inspired algorithms, and sophisticated tactical analysis, this engine achieves superhuman performance while maintaining natural gameplay patterns. Key highlights: • 🧠 Advanced NNUE
https://github.com/dunningkrueg/chess-engine-artificial-intelligence
Last synced: 3 months ago
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A cutting-edge chess engine that combines state-of-the-art AI technologies with grandmaster-level chess understanding. Powered by advanced neural networks, quantum-inspired algorithms, and sophisticated tactical analysis, this engine achieves superhuman performance while maintaining natural gameplay patterns. Key highlights: • 🧠 Advanced NNUE
- Host: GitHub
- URL: https://github.com/dunningkrueg/chess-engine-artificial-intelligence
- Owner: dunningkrueg
- Created: 2025-01-13T13:37:07.000Z (5 months ago)
- Default Branch: main
- Last Pushed: 2025-01-14T14:59:22.000Z (5 months ago)
- Last Synced: 2025-02-08T09:20:20.712Z (4 months ago)
- Language: C++
- Homepage:
- Size: 39.1 KB
- Stars: 3
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🎮 Chess AI Engine
[](https://opensource.org/licenses/MIT)
[](https://isocpp.org/)
[](https://developer.nvidia.com/cuda-toolkit)
[](https://www.openmp.org/)
*A revolutionary chess engine combining quantum computing principles, advanced neural networks, and grandmaster-level strategic understanding.*
[Key Features](#-key-features) • [Installation](#-installation) • [Usage](#-usage) • [Performance](#-performance) • [Contributing](#-contributing)
---
## 🌟 Key Features
### 🧠 Advanced AI Systems
#### Neural Network Architecture
- 🔮 NNUE (Efficiently Updatable Neural Network)
- 🔄 Transformer & Attention Networks
- 🌐 Ensemble Networks
- ⚡ SIMD & AVX2 Optimizations
#### Quantum-Inspired Search
- 🔍 Advanced Alpha-Beta Pruning
- 🎲 Monte Carlo Tree Search
- 🌌 Quantum Search Algorithm
- 💪 Multi-threaded Processing
### 🎯 Strategic & Tactical Excellence
#### Supreme Tactics
- 👁️ Grandmaster Pattern Recognition
- ⚔️ Advanced Sacrifice Analysis
- 🎯 Complex Combination Detection
- 🧮 Deep Tactical Calculation
#### Ultimate Strategy
- 🏰 Deep Positional Understanding
- 📈 Long-term Planning
- ⚖️ Dynamic Imbalance Analysis
- 🔄 Adaptive Play Style
### 🚀 Advanced Features
#### Learning System
- 📚 Real-time Learning
- 📈 Continuous Self-improvement
- 🧩 Pattern Recognition
- 📊 Comprehensive Game Analysis
#### Personality System
- 🎭 Multiple Playing Styles
- 🎯 Opponent Adaptation
- 🔄 Dynamic Strategy Adjustment
- 👑 Grandmaster Emulation
---
## 💻 Requirements
### Software Requirements
```plaintext
✅ Visual Studio 2022
✅ Intel oneAPI Base & HPC Toolkit
✅ CUDA Toolkit (optional, for GPU acceleration)
✅ CMake 3.15 or higher
```
### Hardware Requirements
```plaintext
✅ Modern CPU with AVX2 support
✅ 16GB RAM minimum (32GB recommended)
✅ NVIDIA GPU (optional, for GPU acceleration)
✅ SSD for database storage
```
---
## 🔧 Installation
### 1. Prerequisites Installation
```bash
# Install Visual Studio 2022 with:
- Desktop development with C++
- C++ CMake tools
- Windows SDK
```
### 2. Build Process
```bash
# Clone repository
git clone https://github.com/janebluee/Chess-Engine-Artificial-Intelligence.git
# Create build directory
mkdir build && cd build
# Configure and build
cmake ..
cmake --build . --config Release
```
### 3. Environment Setup
```bash
# Set required environment variables
# Configure paths for optimal performance
```
---
## 📖 Usage
### Basic Implementation
```cpp
// Initialize the engine
ChessEngine engine;
engine.init();
// Get the best move
std::string bestMove = engine.getBestMove(position, depth);
```
### Integration Options
- ♟️ UCI Protocol Compatible
- 🌐 chess.com Integration Ready
- 🖥️ Multiple GUI Support
- 📊 Advanced Analysis Tools
---
## ⚡ Performance
### Benchmarks
```plaintext
🏆 ELO Rating: 4000+
🔍 Search Depth: 40+ ply
⚡ Evaluation Speed: <1ms per position
📈 Multi-core Scaling: Near linear up to 128 threads
```
---
## 🤝 Contributing
We welcome contributions! Please see our [Contributing Guidelines](CONTRIBUTING.md) for details.
---
## 📜 License
This project is licensed under the MIT License - see [LICENSE.md](LICENSE.md) for details.
---
## 🙏 Acknowledgments
- 🎮 Inspired by AlphaZero and Leela Chess Zero
- 🧠 Built upon cutting-edge chess engine research
- 🌌 Incorporates quantum computing principles
- 🔬 Utilizes state-of-the-art AI/ML methodologies
---
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