N Queens

To solve this coding challenge of the N-Queens problem, we need to place n queens on an n x n chessboard such that no two queens can attack each other. This means no two queens can share the same row, column, or diagonal. We aim to find all possible and distinct solutions and represent them in the specified format. The problem requires both a deep understanding of the constraints imposed by queens' movements and an efficient algorithm to explore all possible configurations.

Explanation:

Step-by-Step Explanation

  1. Initialization : We start by initializing an empty
    result
    list to store all valid board configurations. We also prepare an empty
    board
    , which is an n x n matrix filled with '.' representing empty spaces.
  2. Recursive Function : We define a recursive function
    solve(row, cols, diag1, diag2)
    to place queens row by row.
    • Base Case : If
      row
      equals
      n
      , it means we've successfully placed n queens. Convert the current board configuration into a list of strings and append it to
      result
      .
    • Iterate Through Columns : For the current row, we iterate through each column to determine safe positions:
      • Conflict Checks : Use
        cols
        ,
        diag1
        , and
        diag2
        sets to check if the current column or diagonal positions are already attacked by other queens.
        • cols
          keeps track of columns already occupied by queens.
        • diag1
          keeps track of the difference between row and column (r - c), representing the '\' diagonal.
        • diag2
          keeps track of the sum of row and column (r + c), representing the '/' diagonal.
      • Place Queen : If it’s a safe position, place a queen (β€˜Q’) on the board, add the column and diagonals to respective sets, and recursively call
        solve
        for the next row.
      • Backtrack : If placing the queen leads to no solution in subsequent steps, backtrack by removing the queen ('Q') and removing the column and diagonals from respective sets to restore the state.
  3. Starting the Process : Begin the process by calling
    solve(0, set(), set(), set())
    from the first row.
  4. Return Result : After exploring all possibilities, return the
    result
    list containing all the valid board configurations.

Detailed Steps in Pseudocode

Step 1: Initialization
                                            
# Create an empty result list to store all valid configurations
result = []

# Create an empty n x n board filled with '.'
board = [[ '.' for _ in range(n) ] for _ in range(n)]

                                        
Step 2: Define the Recursive Function
                                            
# Define the recursive function to solve the N-Queens problem
def solve(row, cols, diag1, diag2):
    # Check if we have placed queens in all rows
    if row == n:
        # Convert the board to the required format and add to the result list
        result.append([''.join(board[i]) for i in range(n)])
        return
    
    # Iterate through all columns of the current row
    for col in range(n):
        # Check if placing a queen at (row, col) is safe
        if col in cols or (row + col) in diag1 or (row - col) in diag2:
            continue
        
        # Place the queen at (row, col)
        board[row][col] = 'Q'
        
        # Add the column and diagonals to the sets
        cols.add(col)
        diag1.add(row + col)
        diag2.add(row - col)
        
        # Recurse to place the next queen in the next row
        solve(row + 1, cols, diag1, diag2)
        
        # Backtrack by removing the queen
        board[row][col] = '.'
        cols.remove(col)
        diag1.remove(row + col)
        diag2.remove(row - col)

                                        
Step 3: Start the Recursive Process
                                            
# Start the solving process from the first row
solve(0, set(), set(), set())

                                        
Step 4: Return the Result
                                            
# Return all the configurations
return result

                                        
Through this detailed explanation and pseudocode, we attend to the objective of solving the N-Queens problem methodically and ensure we capture each step required, from initialization through recursive backtracking to final solution collection.