八数码问题a*算法python

以下是一个使用A*算法解决八数码问题的Python代码示例：

from queue import PriorityQueue


class State:
    def __init__(self, board, moves=0):
        self.board = board
        self.moves = moves
        self.goal = [[1, 2, 3], [4, 5, 6], [7, 8, 0]]

    def __lt__(self, other):
        return (self.moves + self.h()) < (other.moves + other.h())

    def __eq__(self, other):
        return self.board == other.board

    def __str__(self):
        return '\n'.join([' '.join([str(cell) for cell in row]) for row in self.board])

    def get_blank_pos(self):
        for row in range(3):
            for col in range(3):
                if self.board[row][col] == 0:
                    return row, col

    def clone(self):
        return State([row[:] for row in self.board], self.moves)

    def move(self, dy, dx):
        row, col = self.get_blank_pos()
        row += dy
        col += dx
        if row < 0 or col < 0 or row > 2 or col > 2:
            return None
        else:
            new_board = self.clone().board
            new_board[row][col], new_board[self.get_blank_pos()[0]][self.get_blank_pos()[1]] = \
                new_board[self.get_blank_pos()[0]][self.get_blank_pos()[1]], new_board[row][col]
            return State(new_board, self.moves + 1)

    def h(self):
        return sum([1 if self.board[row][col] != self.goal[row][col] else 0 for col in range(3) for row in range(3)])


def solve(initial_state):
    visited_states = set()
    pq = PriorityQueue()
    pq.put(initial_state)
    while not pq.empty():
        current_state = pq.get()
        if current_state.board == current_state.goal:
            return current_state
        visited_states.add(current_state)
        for dy, dx in [(-1, 0), (1, 0), (0, -1), (0, 1)]:
            neighbor = current_state.move(dy, dx)
            if neighbor is not None and neighbor not in visited_states:
                pq.put(neighbor)
    return None


initial_board = [[1, 2, 3], [4, 0, 6], [7, 5, 8]]
initial_state = State(initial_board)
solution = solve(initial_state)
if solution is None:
    print("No solution found")
else:
    print("Solution found in", solution.moves, "moves\n", solution)

该代码使用了一个`State`类来表示状态，并实现了`__lt__`和`__eq__`方法，以便将状态放入`PriorityQueue`中进行排序。`h()`方法用于计算当前状态与目标状态之间的估计距离，即启发式函数。`solve()`函数使用A*算法进行搜索，直到找到目标状态或队列为空。最后，该代码使用一个具有初始状态的典型八数码问题进行测试。