This project focuses on solving mazes using different algorithms to find the best solution. By leveraging the power of Python and Pygame, it incorporates a visual interface that enhances the understanding and observation of the maze-solving process. The implemented methods include, but are not limited to:

• Depth-First Search (DFS)
• Breadth-First Search (BFS)
• A* Algorithm
• Dijkstra's Algorithm

Each algorithm has its unique approach and benefits, and this project compares their efficiency and effectiveness in navigating through complex mazes.

The use of Pygame allows for a dynamic and interactive visualization of the maze-solving process. Users can watch as the algorithm explores different paths, backtracks when necessary, and eventually discovers the optimal route from the start to the end of the maze. This visual representation makes the abstract concept of algorithms more concrete and understandable.

Python's simplicity and readability make it an excellent choice for implementing these algorithms. The code is structured to be easily extensible, allowing for the addition of more complex maze structures and solving methods in the future.

By combining Python's powerful algorithms with Pygame's visual capabilities, this project not only solves mazes efficiently but also provides an educational tool for understanding algorithmic problem-solving. Whether for educational purposes or as a foundation for more advanced projects, this maze-solving application demonstrates the effective use of technology to tackle classic computational problems.