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https://github.com/ayax537/breadth-first-search-bfs-maze-solver

This Python script implements the Breadth First Search (BFS) algorithm to solve a maze using the Turtle graphics library. The program visually represents the maze and the search process, allowing users to observe how BFS explores paths to find a solution.
https://github.com/ayax537/breadth-first-search-bfs-maze-solver

ai bfs-algorithm bfs-search

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This Python script implements the Breadth First Search (BFS) algorithm to solve a maze using the Turtle graphics library. The program visually represents the maze and the search process, allowing users to observe how BFS explores paths to find a solution.

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# Breadth-First-Search-BFS-Maze-Solver

# Overview

This Python script implements the Breadth First Search (BFS) algorithm to solve a maze using the Turtle graphics library. The program visually represents the maze and the search process, allowing users to observe how BFS explores paths to find a solution.



# Key Components

1. Turtle Graphics Setup

The script creates a Turtle graphics window with:

A black background.

A title "A Maze Solving Program."

Dimensions set to 1300x700 pixels.

2. Maze Representation

The maze is defined using a grid of characters:

+ represents walls.

  (space) represents open paths.

s marks the starting position.

e marks the ending position.

3. Turtle Classes

Five turtle classes are defined to represent different elements of the maze:

Maze (white turtle): Stamps the walls of the maze.

Green turtle: Marks cells that have been visited during the search.

Blue turtle: Indicates frontier cells currently being explored.

Red turtle: Represents the starting position.

Yellow turtle: Represents the ending position and the solution path.

4. Maze Setup Function

The setup_maze function initializes the maze based on the provided grid:

It iterates through each character in the grid, determining the positions of walls, paths, the start, and the end points.

Turtles are moved to their respective positions and stamped to visualize the maze layout.

5. BFS Search Function

The search function implements the BFS algorithm:

It uses a queue (deque) to track the current cells being explored.

The algorithm explores possible moves (up, down, left, right) and marks cells as visited.

If a cell is part of the path and has not been visited, it is added to the queue.

The search continues until the end position is reached.

6. Backtracking to Find the Solution Path

The backRoute function is called once the end is reached:

It retraces the path from the end back to the start, marking the solution path with the yellow turtle.

7. Execution Flow

The maze is set up, the BFS search is performed, and the solution path is visualized.

The program ends when the user clicks on the Turtle graphics window.

# Conclusion

This script serves as an educational tool for understanding how the Breadth First Search algorithm works in the context of maze solving. The visual representation through Turtle graphics makes it engaging and helps illustrate the algorithm's systematic exploration of paths. Users can modify the grid to test different maze configurations, enhancing their understanding of BFS.