This project implements various maze solving algorithms in Python, aiming to find optimal paths through complex maze environments. Maze solving algorithms are fundamental in artificial intelligence applications for pathfinding and navigation.
The project includes implementations and evaluations of several search algorithms to solve mazes. Each algorithm's performance characteristics, computational complexity, and suitability for different maze structures are analyzed and compared.
- Depth-First Search (DFS)
- Breadth-First Search (BFS)
- A* Search Algorithm
- Wall Follower Search Algorithm
- Dijkstra’s Search Algorithm
- Uniform Cost Search (UCS) Search Algorithm
Maze solving algorithms are crucial for pathfinding in AI applications, enabling navigation through complex environments. Evaluating different algorithms provides insights into their strengths, weaknesses, and suitability for specific maze types. Future research could focus on optimizing existing algorithms or developing new approaches for enhanced maze solving efficiency.
- Source Code: Contains Python scripts implementing maze solving algorithms.
- Examples: Sample maze files used for testing algorithms.
- Documentation: Project report and documentation files.