This project implements various search algorithms to solve Sudoku puzzles. It was developed as part of an Artificial Intelligence class to explore different techniques for solving complex problems.
This is a Python-based project that leverages different search algorithms to find solutions for Sudoku puzzles. The implementation includes heuristic algorithms, depth-first search, A*, and more, providing a comprehensive exploration of problem-solving strategies in the context of Sudoku.
The Sudoku puzzles are represented in text files using the following format: 301086504046521070500000001400800002080347900009050038004090200008734090007208103
In this format, each '0' denotes an empty square, and each number represents a filled square, organized in rows.
When visualized as a grid, the above file translates to:
-------------------------
| 3 0 1 | 0 8 6 | 5 0 4 |
| 0 4 6 | 5 2 1 | 0 7 0 |
| 5 0 0 | 0 0 0 | 0 0 1 |
|-------+-------+-------|
| 4 0 0 | 8 0 0 | 0 0 2 |
| 0 8 0 | 3 4 7 | 9 0 0 |
| 0 0 9 | 0 5 0 | 0 3 8 |
|-------+-------+-------|
| 0 0 4 | 0 9 0 | 2 0 0 |
| 0 0 8 | 7 3 4 | 0 9 0 |
| 0 0 7 | 2 0 8 | 1 0 3 |
-------------------------
-Breadth First Search (BFS) -Depth First Search (DFS) -A* -Greedy Search, with 3 variations (row/column completion, cell completion)
- Clone the repository:
git clone - Download the dataset from this link, then place it in the /data folder.
- Install numpy using
pip install numpy - Run main passing as argument the path to the dataset
python main.py path\sudoku_solver\data\sudoku.csv