利用动态调整拦截策略编写python程序实现多搜军舰合作拦截多枚敌方导弹程序，需要添加的变量有军舰位置，导弹拦截成功概率，导弹数量和发射成本，以导弹拦截成功概率最高为优先条件

在Python程序中，我们可以使用列表、字典和优先队列等数据结构来实现军舰合作拦截多枚敌方导弹的动态调整策略。下面是一个简化版的示例：

import heapq

class Missile:
    def __init__(self, position, intercept_probability, launch_cost):
        self.position = position
        self.intercept_probability = intercept_probability
        self.launch_cost = launch_cost

class Frigate:
    def __init__(self, position):
        self.position = position
        self.intercepts_left = float('inf')  # 每艘船初始拦截次数无限大

    def can_intercept(self, missile):
        return self.intercepts_left > 0 and missile.intercept_probability > 0

def calculate_strategy(missiles, frigates):
    priority_queue = []
    for missile in missiles:
        for frigate in frigates:
            if frigate.can_intercept(missile):
                priority = -missile.intercept_probability  # 负概率表示优先级越高
                cost = missile.launch_cost + frigate.intercepts_left * missile.intercept_probability
                heapq.heappush(priority_queue, (priority, cost, missile, frigate))

    while priority_queue:
        _, cost, missile, frigate = heapq.heappop(priority_queue)
        # 实际操作，比如发射拦截物并更新拦截次数
        frigate.intercepts_left -= 1
        print(f"Frigate {frigate.position} successfully intercepted missile {missile.position}. Cost: {cost}")

# 初始化军舰和导弹
missiles = [Missile((x, y), p, c) for x, y, p, c in [(1, 1, 0.8, 10), (2, 2, 0.9, 15)]]
frigates = [Frigate((0, 0)), Frigate((3, 3))]

calculate_strategy(missiles, frigets)

在这个例子中，我们首先创建`Missile`和`Frigate`类，分别存储导弹的位置、拦截概率、发射成本和军舰剩余的拦截次数。然后，我们用一个优先队列`priority_queue`来存储所有的拦截组合，其中优先级由导弹的拦截概率决定。`heapq.heappush`函数会按照优先级自动将元素插入堆顶。

在主循环中，我们不断地从堆中取出拦截组合，执行拦截操作并更新军舰的拦截次数。当所有导弹都被拦截或无剩余拦截机会时，循环结束。