A*算法计算11*13迷宫路径的全部代码

A*算法需要一个网格化的迷宫表示，这里假设迷宫是一个二维列表，1表示墙，0表示可以通过的空格。下面是一个简单的Python代码示例，展示了如何使用A*算法在给定的11x13迷宫中寻找从起点到终点的路径：

import heapq

# 定义迷宫数据
maze = [
    [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
    [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1],  # 起点 (0, 0)
    [1, 0, 1, 1, 1, 1, 1, 1, 1, 1, 1],
    [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1],  # 终点 (2, 9)
    [1, 0, 0, 0, 1, 1, 1, 0, 0, 0, 1],
    [1, 0, 0, 0, 1, 1, 0, 0, 0, 0, 1],
    [1, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1],
    [1, 0, 0, 1, 1, 1, 0, 1, 1, 0, 1],
    [1, 0, 0, 0, 0, 1, 1, 0, 0, 1, 1],
    [1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1],
    [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]
]

# 计算启发式函数值，例如曼哈顿距离
heuristic = lambda pos, goal: abs(pos[0] - goal[0]) + abs(pos[1] - goal[1])

# 函数定义
def a_star_search(maze, start, end):
    frontier = [(0, start)]
    came_from = {}
    cost_so_far = {start: 0}

    while frontier:
        current_cost, current_pos = heapq.heappop(frontier)

        if current_pos == end:
            break

        for next_pos in get_neighbors(maze, current_pos):
            new_cost = current_cost + 1
            if next_pos not in cost_so_far or new_cost < cost_so_far[next_pos]:
                cost_so_far[next_pos] = new_cost
                priority = new_cost + heuristic(next_pos, end)
                heapq.heappush(frontier, (priority, next_pos))
                came_from[next_pos] = current_pos

    path = []
    current_pos = end
    while current_pos != start:
        path.append(current_pos)
        current_pos = came_from.get(current_pos)
    path.append(start)  # 添加起始点
    path.reverse()  # 反转路径顺序
    return path[::-1]  # 返回路径

# 获取邻居函数
def get_neighbors(maze, pos):
    row, col = pos
    neighbors = [(row - 1, col), (row + 1, col), (row, col - 1), (row, col + 1)]
    valid_neighbors = [(r, c) for r, c in neighbors if 0 <= r < len(maze) and 0 <= c < len(maze[0]) and maze[r][c] == 0]
    return valid_neighbors

# 主程序
path = a_star_search(maze, (0, 0), (2, 9))
print("Path from start to end:", path)

这个代码将返回从起点到终点的最短路径。如果迷宫中不存在这样的路径，`a_star_search`函数会返回None。运行此代码前，请确保输入正确的迷宫矩阵。