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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: There are two steps in the naked twins technique. Firstly, we find the naked twins in a unit which are a set of exactly two candidates that are in exactly two boxes in a unit. Secondly, we eliminate the naked twins as possibilities for their peers in the same unit. The above two steps are applied to all the units.

Question 2 (Diagonal Sudoku)

Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: For the diagonal sudoku problem, we have two more units, namely the two main diagonals, in addition to the complete rows, columns, and 3x3 squares. And each box has more peers compared to a regular sudoku. So each time we apply the elimination, only choice and naked twins strategys, we'll go through all the 29 units or more peers.

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

  • solutions.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_values function provided in solution.py

Data

The data consists of a text file of diagonal sudokus for you to solve.

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