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Most often, it is used as an example of a problem that can be solved with a recursive algorithm, by phrasing the n queens problem inductively in terms of adding a single queen to any solution to the problem of placing n−1 queens on an n×n chessboard.
The algorithm searches each potential move for the number of conflicts (number of attacking queens), shown in each square. The algorithm moves the queen to the square with the minimum number of conflicts, breaking ties randomly. Note that the number of conflicts is generated by each new direction that a queen can attack from. If two queens ...
The N queens problem is the problem of placing n chess queens on an n×n chessboard so that no two queens threaten each other. A solution requires that no two queens share the same row, column, or diagonal. It is an example of a generalized exact cover problem. [5]
The classic textbook example of the use of backtracking is the eight queens puzzle, that asks for all arrangements of eight chess queens on a standard chessboard so that no queen attacks any other. In the common backtracking approach, the partial candidates are arrangements of k queens in the first k rows of the board, all in different rows and ...
Algorithm X is a recursive, nondeterministic, depth-first, backtracking algorithm that finds all solutions to the exact cover problem. Some of the better-known exact cover problems include tiling , the n queens problem , and Sudoku .
The min-conflicts algorithm is a local search algorithm specific for CSPs and is based on that principle. In practice, local search appears to work well when these changes are also affected by random choices. An integration of search with local search has been developed, leading to hybrid algorithms.
The most famous problem of this type is the eight queens puzzle. Problems are further extended by asking how many possible solutions exist. Further generalizations apply the problem to NxN boards. [3] [4] An 8×8 chessboard can have 16 independent kings, 8 independent queens, 8 independent rooks, 14 independent bishops, or 32 independent ...
The cache prevents duplicate executions for equivalent sub-graphs. Without any duplicates, the algorithms can operate in a time that is proportional to the size of graphs, as shown in Figure 9 and 10. Figure 9: Results in N-Queens Problem Figure 10: Performance of ZDDs vs that of BDDs