# N-Queen Problem Using Python Without Recursion The N-Queen problem is a classical problem in computer science and artificial intelligence that demonstrates the concepts of state-space search, constraint satisfaction, and backtracking. The problem is to place N queens on an N × N chessboard in such a way that no two queens attack each other. In chess, a queen can attack another queen if both are placed in the same row, the same column, or the same diagonal. Therefore, a valid solution must satisfy all these constraints simultaneously. In a Programming and AI Lab, the N-Queen problem is useful for understanding how an intelligent system can search through a large number of possible states and eliminate invalid states. The usual solution uses recursion to implement backtracking. However, the problem can also be solved without recursion by using an explicit stack. The stack performs the same task that the system call stack normally performs during recursive backtracking. The basic idea is to place one queen in each row. Since every row contains exactly one queen, we only need to decide the column in which the queen of each row should be placed. Before placing a queen, we check whether its position is safe. A position is safe when no previously placed queen exists in the same column or on either diagonal. For a board of size N, the possible positions form a search space. At every row, the algorithm tries different columns. If a safe position is found, the queen is placed and the algorithm moves to the next row. If no safe position is available, the algorithm backtracks to the previous row, removes the previously placed queen, and tries another column. In the non-recursive implementation, this backtracking information is maintained explicitly using a stack. The following Python program solves the N-Queen problem without using recursion. It uses a list as a stack and stores the column selected for each row. ```python def is_safe(queens, row, col): for previous_row in range(row): previous_col