Artificial Intelligence Nanodegree

Introductory Project: Diagonal Sudoku Solver

Question 1 (Naked Twins)

Q: How do we use constraint propagation to solve the naked twins problem?

A: If two boxes in a unit of the unitlist contain an identical pair of candidates and only those two candidates, then no other boxes in that group could be those values. These 2 candidates can be excluded from other boxes in the unit.

1. Find all identical pairs in boxes belonging to one rowunit, columnunit or squareunit
2. Find all boxes in a rowunit, columnunit or squareunit that are holding on of the numbers of the identified naked twins and delete this value from those boxes
3. The whole Sudoku can be solved using the eliminate() and the naked_twins() function repeatedly until the Sudoku is solved.

Question 2 (Diagonal Sudoku)

Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: The constraint here are the two diagonals arrays. So we need to add them to the unitlist, so that the algorithm also takes care of the diagonals as units.

1. Find the boxes for the diagonals
2. Add them to the unitlist and eliminate() and the naked_twins() function repeatedly until the Sudoku is solved.

Install

This project requires Python 3.

We recommend students install Anaconda, a pre-packaged Python distribution that contains all of the necessary libraries and software for this project. Please try using the environment we provided in the Anaconda lesson of the Nanodegree.

Optional: Pygame

Optionally, you can also install pygame if you want to see your visualization. If you've followed our instructions for setting up our conda environment, you should be all set.

If not, please see how to download pygame here.

Code

• solution.py - You'll fill this in as part of your solution.
• solution_test.py - Do not modify this. You can test your solution by running python solution_test.py.
• PySudoku.py - Do not modify this. This is code for visualizing your solution.
• visualize.py - Do not modify this. This is code for visualizing your solution.

Visualizing

To visualize your solution, please only assign values to the values_dict using the assign_value function provided in solution.py

Submission

Before submitting your solution to a reviewer, you are required to submit your project to Udacity's Project Assistant, which will provide some initial feedback.

The setup is simple. If you have not installed the client tool already, then you may do so with the command pip install udacity-pa.

To submit your code to the project assistant, run udacity submit from within the top-level directory of this project. You will be prompted for a username and password. If you login using google or facebook, visit this link for alternate login instructions.

This process will create a zipfile in your top-level directory named sudoku-.zip. This is the file that you should submit to the Udacity reviews system.