🧩 AI Pathfinding Visualizer (BFS Algorithm)

An interactive grid-based pathfinding visualizer built with Python and Pygame. This project demonstrates how the Breadth-First Search (BFS) algorithm explores a search space and guarantees finding the optimal (shortest) path in an unweighted grid, even when faced with complex asymmetrical mazes.

---

🚀 Features

• Real-time BFS Visualization: Step-by-step exploration of nodes across the grid space.
• Guaranteed Optimal Path: Highlights the shortest route from the start node to the destination.
• Custom Maze Layouts: Implements asymmetrical wall structures to showcase the difference between optimal and suboptimal paths.
• Interactive UI: Dynamic rendering of visited nodes, active paths, and final route using Pygame.

---

🛠️ Tech Stack

• Language: Python 3.12+
• GUI Engine: pygame-ce (Pygame Community Edition)
• Data Structures: Queue (deque), NumPy arrays

---

📦 Installation & Setup

1. Clone the repository: git clone https://github.com/shresthajitendra/AI-Pathfinding-Visualizer-Pygame.git

2. Go to project directory: cd AI-Pathfinding-Visualizer-Pygame

3. Install dependencies: pip install pygame-ce numpy

4. Run the visualizer: python main.py

---

📜 Next Steps

• Add Reinforcement Learning (Q-Learning) agent for comparative pathfinding.
• Implement A* and Dijkstra algorithms.