A sudoku is an n×n grid (normally 9×9) with some numbers initially placed – these cannot
be changed. The grid is broken down into sub-blocks of equal size. Solving the puzzle
requires ﬁnding numbers from 1 to n such that each number appears exactly once in each
row, column and sub-block or declaring that the Sudoku is unsolvable. Below is an
example of a 9×9 sudoku.
In this assignment you will implement an AI that can solve 9×9 sudoku puzzles using
search algorithms that you have seen in the unit so far (Breadth- and depth-ﬁrst search,
Heuristic search, informed search: Greedy, A* search, local search, or any other method
you deem suitable).
Your code will be subject to automated testing on example grids which have various
diﬃculties. More details can be found in the Jupyter Notebook ﬁle.
Download and extract the sudoku.zip ﬁle on this page, and open sudoku.ipynb to begin.
Ensure you read the guidelines carefully.
You must submit your completed Jupyter notebook (.ipynb) ﬁle.
• You should restart the kernel and run all cells before submission.
• You must not delete or modify any of the blank test cells.
• You do not have to write your code in the Jupyter environment. You are welcome to
write your solution in another IDE, but you must copy it across and test it within the
Jupyter notebook before submission.
Additionally submit any other ﬁles as required to get your solution to work, or as speciﬁed
in the notebook (e.g. readme ﬁles).
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