Astar算法的伪代码

当然，下面是A*算法的伪代码：

function AStar(start, goal):
    // 初始化开放列表和关闭列表
    openList := [start]
    closedList := []

    // 初始化起始节点的代价和父节点
    start.g := 0
    start.h := heuristic(start, goal)
    start.f := start.g + start.h
    start.parent := null

    while openList is not empty:
        // 选择F值最小的节点
        current := node with minimum f value in openList

        // 找到目标节点，路径找到
        if current == goal:
            return constructPath(current)

        // 将当前节点从开放列表移到关闭列表
        remove current from openList
        add current to closedList

        // 遍历当前节点的邻居
        for each neighbor in current.neighbors:
            if neighbor in closedList:
                continue

            // 计算邻居节点的代价
            tentative_g := current.g + distance(current, neighbor)

            if neighbor not in openList or tentative_g < neighbor.g:
                // 更新邻居节点的代价和父节点
                neighbor.g := tentative_g
                neighbor.h := heuristic(neighbor, goal)
                neighbor.f := neighbor.g + neighbor.h
                neighbor.parent := current

                if neighbor not in openList:
                    // 将邻居节点加入开放列表
                    add neighbor to openList

    // 开放列表为空，无路径可到达目标节点
    return null

function constructPath(node):
    path := []
    while node is not null:
        add node to path
        node := node.parent
    return reversed(path)

这是A*算法的基本伪代码，它采用启发式函数（heuristic function）来评估节点的优先级。这个算法在搜索路径时综合了节点的代价和预测的剩余代价，并且通过优先考虑具有较小F值的节点来选择下一个节点进行扩展。