撰写代码实现AI贪吃蛇寻路

要实现AI贪吃蛇寻路，可以使用A*算法。具体步骤如下：

1. 将地图抽象成一个网格图，每个格子表示一个状态。
2. 将贪吃蛇的头部作为起点，食物作为终点。
3. 使用A*算法搜索最短路径，其中启发函数可以使用曼哈顿距离或欧几里得距离。
4. 在搜索过程中需要考虑贪吃蛇的身体，不能穿过自己的身体。

以下是伪代码实现：

function A_star(start, end, obstacles):
    open_list = [start]
    closed_list = []
    g_score = {start: 0}
    f_score = {start: heuristic(start, end)}
    parent = {}

    while open_list:
        current = min(open_list, key=lambda x: f_score[x])
        if current == end:
            return reconstruct_path(parent, end)

        open_list.remove(current)
        closed_list.append(current)

        for neighbor in get_neighbors(current, obstacles):
            if neighbor in closed_list:
                continue

            tentative_g_score = g_score[current] + 1
            if neighbor not in open_list or tentative_g_score < g_score[neighbor]:
                parent[neighbor] = current
                g_score[neighbor] = tentative_g_score
                f_score[neighbor] = tentative_g_score + heuristic(neighbor, end)

                if neighbor not in open_list:
                    open_list.append(neighbor)

    return None

function get_neighbors(current, obstacles):
    neighbors = []
    for dx, dy in [(0, 1), (0, -1), (1, 0), (-1, 0)]:
        x, y = current[0] + dx, current[1] + dy
        if (x, y) not in obstacles:
            neighbors.append((x, y))
    return neighbors

function heuristic(a, b):
    return abs(a[0] - b[0]) + abs(a[1] - b[1])

function reconstruct_path(parent, end):
    path = [end]
    while end in parent:
        end = parent[end]
        path.append(end)
    return path[::-1]