动态规划百度百科的解释
var minCostClimbingStairs = function(arr) {
// 大事化小
//dp[n] 到第n层阶梯 花费最少
var len = arr.length
var dp = []
dp[0] = 0
dp[1] = 0
for(var i = 2;i<=len;i++){
dp[i] = Math.min(dp[i-2]+arr[i-2],dp[i-1]+arr[i-1])
}
return dp[len]
};
var maxProfit = function(prices) {
//max - min
// prices[i] - min
var min = prices[0]
var maxValue = 0
for(var i=0;i<prices.length;i++){
if(prices[i] < min){
min = prices[i]
}else{
maxValue = Math.max(maxValue,prices[i] - min)
}
}
return maxValue
};
动态规划 + 数学归纳法
两个字符串 各自取任意长度,对应的最优质递推过程,这里使用了二维数组的思想
var longestCommonSubsequence = function(text1, text2) {
const m = text1.length, n = text2.length;
const dp = new Array(m + 1).fill().map(() => new Array(n + 1).fill(0));
//'abcbdab','bdcaba'
for (let i = 1; i <= m; i++) {
for (let j = 1; j <= n; j++) {
if (text1[i - 1] === text2[j - 1]) {
dp[i][j] = dp[i - 1][j - 1] + 1;
} else {
dp[i][j] = Math.max(dp[i - 1][j], dp[i][j - 1]);
}
}
}
return dp[m][n];
};
插入排序 + 动态规划 的思想
var lengthOfLIS = function (nums) {
var len = nums.length;
if (len == 0) {
return 0;
}
var dp = new Array(len).fill(1);
var maxLen = 1;
for (var i = 1; i < len; i++) {
for (var j = 0; j < i; j++) {
if (nums[i] > nums[j]) {
dp[i] = Math.max(dp[i], dp[j] + 1);
}
}
maxLen = Math.max(maxLen, dp[i]);
}
return maxLen;
};
console.log(lengthOfLIS([10, 2, 3, 5]));