https://github.com/ayax537/a-pathfinding-algorithm-for-maze-solving

This Python script implements the A* pathfinding algorithm using the Turtle graphics library to visually solve a maze. The program sets up a maze defined by a grid and animates the search process, demonstrating how the A* algorithm finds the shortest path from a starting point to an endpoint.
https://github.com/ayax537/a-pathfinding-algorithm-for-maze-solving

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This Python script implements the A* pathfinding algorithm using the Turtle graphics library to visually solve a maze. The program sets up a maze defined by a grid and animates the search process, demonstrating how the A* algorithm finds the shortest path from a starting point to an endpoint.

• Host: GitHub
• URL: https://github.com/ayax537/a-pathfinding-algorithm-for-maze-solving
• Owner: ayax537
• Created: 2024-11-11T09:11:23.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2024-11-11T09:12:46.000Z (about 2 months ago)
• Last Synced: 2024-11-11T10:23:41.519Z (about 2 months ago)
• Topics: ai
• Language: Python
• Homepage:
• Size: 4.88 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# A-Pathfinding-Algorithm-for-Maze-Solving

# Description

This Python script implements the A* pathfinding algorithm using the Turtle graphics library to visually solve a maze. The program sets up a maze defined by a grid and animates the search process, demonstrating how the A* algorithm finds the shortest path from a starting point to an endpoint.

# Key Features

1. Maze Setup

The maze is represented as a grid of characters, where:

+ represents walls.

  (space) represents open paths.

s represents the start position.

e represents the end position.

2. Turtle Graphics

The program uses Turtle graphics to visually represent the maze and the search process:

White Turtle: Represents the maze walls.

Green Turtle: Marks visited cells during the search.

Blue Turtle: Indicates the frontier cells being explored.

Red Turtle: Marks the start position and follows the path.

Yellow Turtle: Represents the end position and the solution path.

3. A Algorithm*

The A* algorithm combines features of Dijkstra's algorithm and a heuristic approach to efficiently find the shortest path:

Heuristic Function: Uses Manhattan distance to estimate the cost from the current cell to the goal.

Priority Queue: Maintains a queue of nodes to be explored, prioritized by their estimated total cost (actual cost + heuristic cost).

The algorithm explores neighboring cells (up, down, left, right) and updates paths based on costs.

4. Animation and Visualization

The search process is animated, showing the algorithm's progression through the maze:

As cells are visited, they are marked with the green turtle.

The path to the endpoint is highlighted with the yellow turtle once the goal is reached.

5. Backtracking

After reaching the endpoint, the program backtracks to visualize the complete path from the start to the end using the yellow turtle.

# Conclusion

This script provides a practical implementation of the A* algorithm in a visually engaging manner, making it an excellent educational tool for understanding pathfinding techniques. The use of Turtle graphics adds an interactive element, allowing users to observe the algorithm's decision-making process in real-time. The program can be adapted to different maze configurations by modifying the grid definitions.