In this project, we explore real-world applications of Depth-First Search (DFS), mazes, and pathfinding algorithms.
Depth-First Search is a graph traversal algorithm used to explore nodes in a systematic manner. It starts at the root node and explores as far as possible along each branch before backtracking. DFS is often used in maze-solving and graph traversal applications.
A maze is a complex, branching puzzle that includes choices of paths and dead ends. In the context of this project, a maze is represented as a grid of cells, where some cells are walls, and others are open paths.
Pathfinding is the process of finding a path from a starting point to a destination point in a maze or graph. Different algorithms, such as DFS and Breadth-First Search (BFS), are used to find the most efficient path.
The project employs the DFS algorithm to solve mazes. The DFS algorithm explores the maze, trying to find a path from the start cell to the goal cell. It backtracks when it reaches dead-ends and keeps exploring other paths until it finds a solution.
The DFS solver explores the maze, and after backtracking and exploration, it finds a path to the goal cell.
This project uses the pyamaze library to create mazes, visualize the exploration process, and find the path. The code provided in the src repository demonstrates how to create a maze, apply the DFS algorithm to solve it, and visualize the results.
|
|