python 八数码 深度优先搜索

以下是使用Python实现深度优先搜索算法解决八数码问题的示例代码：

# 定义八数码问题的初始状态和目标状态
start_state = [2, 8, 3, 1, 6, 4, 7, 0, 5]
goal_state = [1, 2, 3, 8, 0, 4, 7, 6, 5]

# 定义节点类
class Node:
    def __init__(self, state, parent, action):
        self.state = state
        self.parent = parent
        self.action = action

    def expand(self):
        # 定义移动操作
        def move_up(state):
            new_state = state[:]
            index = new_state.index(0)
            if index not in [0, 1, 2]:
                new_state[index - 3], new_state[index] = new_state[index], new_state[index - 3]
                return new_state
            else:
                return None
        def move_down(state):
            new_state = state[:]
            index = new_state.index(0)
            if index not in [6, 7, 8]:
                new_state[index + 3], new_state[index] = new_state[index], new_state[index + 3]
                return new_state
            else:
                return None

        def move_left(state):
            new_state = state[:]
            index = new_state.index(0)
            if index not in [0, 3, 6]:
                new_state[index - 1], new_state[index] = new_state[index], new_state[index - 1]
                return new_state
            else:
                return None

        def move_right(state):
            new_state = state[:]
            index = new_state.index(0)
            if index not in [2, 5, 8]:
                new_state[index + 1], new_state[index] = new_state[index], new_state[index + 1]
                return new_state
            else:
                return None

        # 调用移动操作，生成新节点
        successors = []
        for move in [move_up, move_down, move_left, move_right]:
            new_state = move(self.state)
            if new_state is not None:
                successors.append(Node(new_state, self, move))
        return successors

# 定义深度优先搜索算法
def dfs(start_state, goal_state):
    start_node = Node(start_state, None, None)
    if start_state == goal_state:
        return start_node
    frontier = [start_node]
    explored = set()
    while frontier:
        node = frontier.pop()
        explored.add(tuple(node.state))
        for child in node.expand():
            if tuple(child.state) not in explored:
                if child.state == goal_state:
                    return child
                frontier.append(child)
    return None

# 调用深度优先搜索算法，并输出结果
result_node = dfs(start_state, goal_state)
if result_node is None:
    print("No solution found.")
else:
    path = []
    node = result_node
    while node is not None:
        path.append(node)
        node = node.parent
    path.reverse()
    print("Solution found with", len(path) - 1, "moves:")
    for i, node in enumerate(path):
        if i == 0:
            print("Start state:")
        elif i == len(path) - 1:
            print("Goal state:")
        else:
            print("Move", i, ":", node.action.__name__)
        print(node.state[0:3])
        print(node.state[3:6])
        print(node.state[6:9])
        print("")

运行以上代码，即可使用深度优先搜索算法解决八数码问题。