ShihanUTSA / AIND-Sudoku

My solutions for the Udacity- Artificial Intelligence Nano Degree (AIND)(Sudoku-Solver)

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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: First access each unit in the unitlist and search for strings with two same digits. Then access each peer in the unit which string length should not be one (string length one means already resolved box) and remove the above two digits if they are present.

Question 2 (Diagonal Sudoku)

Q: How do we use constraint propagation to solve the diagonal sudoku problem?
A: The straight forward method to incoporate diagonal constraint is to define 2 diagonals in the board as units and include them in the unitlist. This will make two new sets of peers using diagonal boxes and increase the constraints (reduce the freedom of search) in the search space.

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_values 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](https://project-assistant.udacity.com/auth_tokens/jwt_login 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.

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My solutions for the Udacity- Artificial Intelligence Nano Degree (AIND)(Sudoku-Solver)


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