代价树搜索生活应用实例python代码

下面是一个代价树搜索的生活应用实例的 Python 代码，该代码可以帮助你找到最便宜的购物路径：

import heapq

# 商品价格表
prices = {
    "apple": 2,
    "banana": 1,
    "pear": 3,
    "orange": 2.5,
    "grape": 4,
    "watermelon": 5,
    "pineapple": 6
}

# 路径图
graph = {
    "home": {"market": 5},
    "market": {"apple": 2, "banana": 1, "pear": 3, "orange": 2.5},
    "apple": {"market": 2},
    "banana": {"market": 1},
    "pear": {"market": 3},
    "orange": {"market": 2.5},
    "grape": {"market": 4},
    "watermelon": {"market": 5},
    "pineapple": {"market": 6}
}

# 代价树搜索算法
def search(start, goal):
    frontier = []
    heapq.heappush(frontier, (0, start))
    explored = set()
    
    while frontier:
        cost, node = heapq.heappop(frontier)
        if node == goal:
            return cost
        explored.add(node)
        for neighbor, neighbor_cost in graph[node].items():
            if neighbor not in explored:
                total_cost = cost + neighbor_cost
                heapq.heappush(frontier, (total_cost, neighbor))

# 找到最便宜的购物路径
def cheapest_shopping_list(shopping_list):
    total_cost = 0
    for item in shopping_list:
        cost = search("home", "market") + prices[item] + search("market", item)
        total_cost += cost
    return total_cost

# 测试代码
shopping_list = ["apple", "banana", "watermelon", "pineapple"]
total_cost = cheapest_shopping_list(shopping_list)
print("最便宜的购物路径是:", shopping_list, "，总价是:", total_cost)

在上面的代码中，我们使用了一个商品价格表和一个路径图来表示我们要购买的商品和购买它们的路径。我们使用了代价树搜索算法来找到每个商品的购买代价，并将它们相加得到最终的总购买代价。