The Maze Path Solver utilizes a popular algorithm called Depth-First Search (DFS) to explore and find the optimal path through the maze. DFS is an algorithm for traversing or searching tree or graph data structures. In the context of maze solving, DFS explores the maze by continuously moving forward until it reaches a dead end, then it backtracks and explores another path.
The project consists of a Java class that takes a maze as input and outputs the shortest path from the starting point to the ending point. The maze is represented as a 2D grid, where each cell can be either a wall or an empty space.
1. Maze Solver Algorithm: The project implements the Depth-First Search (DFS) algorithm to explore and find the shortest path in the maze. DFS guarantees that it will find the shortest path between the starting and ending points.
2. Input Maze Handling: The project accepts a 2D grid maze as input, represented as a rectangular grid of cells. Each cell can be either a wall or an empty space, defining the maze's structure.
3. Optimal Path Output: The project outputs the shortest path between the starting and ending points as a sequence of coordinates. These coordinates represent the optimal route to traverse the maze and reach the destination.
4. Flexibility: The Maze Path Solver can handle mazes of any size, accommodating different complexities and grid dimensions.
1. Provide Input Maze: Initialize the Maze Path Solver with the input maze, either by passing it as a file or as an array/structure representing the grid.
2. Find the Shortest Path: Execute the Maze Path Solver to find the shortest path between the starting and ending points.
3. Retrieve Optimal Path: Access the resulting optimal path as a sequence of coordinates or as desired based on your implementation.
4. This project facilitates solving maze problems efficiently by providing a clear and concise Java implementation that finds the shortest path between the specified start and end points in a 2D grid maze. It can be extended and customized to incorporate additional features or algorithms for more complex maze-solving scenarios.
5. Feel free to enhance and contribute to the project, as it is open-source and available under the MIT License.