题目地址: https://leetcode.com/problems/burst-balloons/description/
题目描述:
Given n
balloons, indexed from 0
to n-1
. Each balloon is painted with a number on it represented by array nums
. You are asked to burst all the balloons. If the you burst balloon i
you will get nums[left] * nums[i] * nums[right]
coins. Here left
and right
are adjacent indices of i
. After the burst, the left
and right
then becomes adjacent.
Find the maximum coins you can collect by bursting the balloons wisely.
Note:
- You may imagine nums[-1] = nums[n] = 1. They are not real therefore you can not burst them.
- 0 ≤ n ≤ 500, 0 ≤ nums[i] ≤ 100
Example:
Input: [3,1,5,8]
Output: 167
Explanation: nums = [3,1,5,8] --> [3,5,8] --> [3,8] --> [8] --> []
coins = 3*1*5 + 3*5*8 + 1*3*8 + 1*8*1 = 167
题目大意
打气球游戏,当我们打某个位置的气球的时候,能获得它左右两个气球上的分数和自身分数的乘积。问如何打气球能获得最多的分数?可以认为最左右两边隐含着分数为1不用打破的气球。
解题方法
这个是个DP的题目,当然也可以通过记忆化搜索的方式解决。
令dfs(i, j) 和 c[i][j]是在第[i, j]闭区间上打破气球能获得最大值。那么,在其中找到一个不打破的气球k,则可以得到以下关系:
c[i][j] = max(c[i][j], self.dfs(nums, c, i, k - 1) + nums[i - 1] * nums[k] * nums[j + 1] + self.dfs(nums, c, k + 1, j))
含义是,我们找出在[i, k - 1]、[k + 1, j]闭区间打气球的分数最大值,然后会把第i - 1和第j + 1个气球保留下来,让这两个气球和第k个气球相乘,最后求三个加法。
模拟左右两边的气球的方法是直接添加上首尾各一个1,同时使用记忆化能加速不少,也为下一步的DP提供思路。
时间复杂度是O(N^2 * log(N))(不会算…),空间复杂度是O(N)。
class Solution(object):
def maxCoins(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
n = len(nums)
nums.insert(0, 1)
nums.append(1)
c = [[0] * (n + 2) for _ in range(n + 2)]
return self.dfs(nums, c, 1, n)
def dfs(self, nums, c, i, j):
if i > j: return 0
if c[i][j] > 0: return c[i][j]
if i == j: return nums[i - 1] * nums[i] * nums[i + 1]
res = 0
for k in range(i, j + 1):
res = max(res, self.dfs(nums, c, i, k - 1) + nums[i - 1] * nums[k] * nums[j + 1] + self.dfs(nums, c, k + 1, j))
c[i][j] = res
return c[i][j]
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第二种解法是使用DP。
DP一般都可以通过记忆化搜索来改出来,但是我不会。。很遗憾,参考了别人的代码,还是没搞懂。。
class Solution(object):
def maxCoins(self, nums):
"""
:type nums: List[int]
:rtype: int
"""
n = len(nums)
nums.insert(0, 1)
nums.append(1)
dp = [[0] * (n + 2) for _ in range(n + 2)]
for len_ in range(1, n + 1):
for left in range(1, n - len_ + 2):
right = left + len_ - 1
for k in range(left, right + 1):
dp[left][right] = max(dp[left][right], dp[left][k - 1] + nums[left - 1] * nums[k] * nums[right + 1] + dp[k + 1][right])
return dp[1][n]
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参考资料:
http://www.cnblogs.com/grandyang/p/5006441.html https://www.youtube.com/watch?v=z3hu2Be92UA
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