👑 N-Queens Visualizer AI

Visualize the classic N-Queens problem using AI search algorithms (Hill Climbing, Simulated Annealing, Local Beam Search) in real time with Pygame.

---

🎮 Features & Highlights

• 👑 N-Queens Problem: Place one queen per row/column with zero conflicts.

• 🔍 Search Algorithms:

  • Hill Climbing with random restarts
  • Simulated Annealing with customizable temperature schedule
  • Local Beam Search with user-defined beam width

• ⏱️ Performance Metrics: Iterations, restarts, and solve time printed in console.

• 🎨 Graphical Board: Pygame-based animation of algorithm progress.

• ⚙️ Configurable: Board size, algorithm parameters, timer interval.

---

🛠️ Tech Stack

• Language: Python 3.7+
• Graphics: Pygame
• Computation: NumPy

---

📥 Installation & Setup

1. Clone the repository

   git clone https://github.com/asadsandhu/n-queens-ai.git
   cd n-queens-visualizer

2. Create & activate virtual environment (recommended)

   python3 -m venv venv
   source venv/bin/activate    # macOS/Linux
   venv\\Scripts\\activate   # Windows

3. Install dependencies

   pip install -r requirements.txt

---

🎮 Running the Visualizer

python n_queens_visualizer.py

1. Select Algorithm: Uncomment your choice in main():

   # hill_climbing(initial_board)
   simulated_annealing(initial_board, initial_temp=100.0, cooling_rate=0.95)
   # local_beam_search(k, initial_states)

2. Adjust Parameters: Modify BOARD_SIZE, initial_temp, cooling_rate, or beam width k at top of script.

3. Watch: The board updates every 500ms showing queen placements and conflict counts.

---

⚙️ Configuration & Customization

• BOARD_SIZE: Change number of queens/rows (modify related constants).

• Timer Interval: Adjust pygame.time.set_timer(pygame.USEREVENT, interval_ms) for speed.

• Algorithm Params:

  • initial_temp, cooling_rate for simulated annealing
  • k, initial_states count for local beam search

---

📂 Project Structure

n-queens-visualizer/
├── README.md               # Project overview & instructions
├── n_queens_visualizer.py  # Main visualization & AI logic
├── queen.png               # Queen sprite image
├── requirements.txt        # pygame, numpy
├── .gitignore              # __pycache__, venv/
└── assets/
    └── (optional) GIFs/screenshots

---

🤝 Contributing

1. ⭐ Star the repo
2. 🍴 Fork
3. 💡 Create a feature branch
4. 🚀 Commit & push
5. 🔃 Open a Pull Request

Please follow PEP 8 style and include examples/tests for new algorithms.

---

📄 License

Distributed under the MIT License. See LICENSE for details.