An AI agent that uses constraint propagation and binary search trees to solve Sudoku puzzles.
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README.md

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: Constraint propagation is used to solve this problem by eliminating all peer values that are shared by their naked twin brethren followed by choosing one of the two options for the values to be present in the naked twins. Since this presents two possible scenarios, a tree of scenarios must be traversed to find a valid solution.

Question 2 (Diagonal Sudoku)

Q: How do we use constraint propagation to solve the diagonal Sudoku problem?
A: Constraint propagation is used to solve this problem by adding in the extra units of the diagonal to the existing row, column, and square units. By doing so, those subspaces are referred to when the elimination and choose-one strategies are employed during propagation to a solution.

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 - Fill in the required functions in this file to complete the project.
  • test_solution.py - You can test your solution by running python -m unittest.
  • PySudoku.py - This is code for visualizing your solution.
  • visualize.py - 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.