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Python scripts for solving the Sudoku problem exploiting constraint satisfaction and simulated annealing.

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Sudoku-solver

A sudoku puzzle is composed of a square 9x9 board divided into 3 rows and 3 columns of smaller 3x3 boxes. The goal is to fill the board with digits from 1 to 9 such that:

  • each number appears only once for each row column and 3x3 box;
  • each row, column, and 3x3 box should containing all 9 digits. The solver should take as input a matrix where empty squares are represented by a standard symbol (e.g., ".", "_", or "0"), while known square should be represented by the corresponding digit (1,...,9).

Write a solver for sudoku puzzles using a constraint satisfaction approach based on constraint propagation and backtracking, and any one of your choice between the following approaches:

  1. simulated annealing;
  2. genetic algorithms;
  3. continuous optimization using gradient projection.

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Python scripts for solving the Sudoku problem exploiting constraint satisfaction and simulated annealing.

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