[抄题]:

On an NxN chessboard, a knight starts at the r-th row and c-th column and attempts to make exactly Kmoves. The rows and columns are 0 indexed, so the top-left square is (0, 0), and the bottom-right square is (N-1, N-1).

A chess knight has 8 possible moves it can make, as illustrated below. Each move is two squares in a cardinal direction, then one square in an orthogonal direction.

Each time the knight is to move, it chooses one of eight possible moves uniformly at random (even if the piece would go off the chessboard) and moves there.

The knight continues moving until it has made exactly K moves or has moved off the chessboard. Return the probability that the knight remains on the board after it has stopped moving.

Example:

Input: 3, 2, 0, 0
Output: 0.0625
Explanation: There are two moves (to (1,2), (2,1)) that will keep the knight on the board.
From each of those positions, there are also two moves that will keep the knight on the board.
The total probability the knight stays on the board is 0.0625.

[暴力解法]:

时间分析:

空间分析:

[优化后]:

时间分析:

空间分析:

[奇葩输出条件]:

[奇葩corner case]:

[思维问题]:

以为就是数学题算一下就行了。没想到每走一步,棋盘都要变化,所以要用2个dp数组:初始和现在。

[英文数据结构或算法,为什么不用别的数据结构或算法]:

[一句话思路]:

没想到每走一步,棋盘都要变化,所以要用2个dp数组:初始和现在。进行坐标型dp。

[输入量]:空: 正常情况:特大:特小:程序里处理到的特殊情况:异常情况(不合法不合理的输入):

[画图]:

[一刷]:

  1. ij是新扩展的,row col是原来已有的。所以要用新扩展的+原来已有的。
  2. 答案要求小数时,初始化数组为double型。

[二刷]:

[三刷]:

[四刷]:

[五刷]:

[五分钟肉眼debug的结果]:

[总结]:

没想到每走一步,棋盘都要变化,所以要用2个dp数组:初始和现在。

[复杂度]:Time complexity: O(n2) Space complexity: O(n2)

[算法思想:迭代/递归/分治/贪心]:

[关键模板化代码]:

二维矩阵需要一行行地填:

for (double[] row : dp0) {
Arrays.fill(row, 1);
}

[其他解法]:

[Follow Up]:

[LC给出的题目变变变]:

[代码风格] :

[是否头一次写此类driver funcion的代码] :

[潜台词] :

class Solution {
int[][] directions = {{1, 2}, {1, -2}, {2, - 1}, {2, 1}, {-1, 2}, {-1, -2}, {-2, 1}, {-2, -1}};
public double knightProbability(int N, int K, int r, int c) {
//corner case //initialization: len, dp0[][] and fill with 1
double[][] dp0 = new double[N][N];
for (double[] row : dp0) {
Arrays.fill(row, 1);
} //calculate dp1, give to dp0
for (int l = 0; l < K; l++) {
double[][] dp1 = new double[N][N];
for (int i = 0; i < N; i++) {
for (int j = 0; j < N; j++) {
for (int[] d : directions) {
int row = i + d[0];
int col = j + d[1];
if (valid(row, col, N)) dp1[i][j] += dp0[row][col];
}
}
}
dp0 = dp1;
}
return dp0[r][c] / (Math.pow(8, K));
} public boolean valid(int x, int y, int len) {
if (0 <= x && x < len && 0 <= y && y < len) return true;
return false;
}
}

688. Knight Probability in Chessboard棋子留在棋盘上的概率的更多相关文章

  1. leetcode 576. Out of Boundary Paths 、688. Knight Probability in Chessboard

    576. Out of Boundary Paths 给你一个棋盘,并放一个东西在一个起始位置,上.下.左.右移动,移动n次,一共有多少种可能移出这个棋盘 https://www.cnblogs.co ...

  2. 【LeetCode】688. Knight Probability in Chessboard 解题报告(Python)

    作者: 负雪明烛 id: fuxuemingzhu 个人博客: http://fuxuemingzhu.cn/ 题目地址:https://leetcode.com/problems/knight-pr ...

  3. LeetCode 688. Knight Probability in Chessboard

    原题链接在这里:https://leetcode.com/problems/knight-probability-in-chessboard/description/ 题目: On an NxN ch ...

  4. 688. Knight Probability in Chessboard

    On an NxN chessboard, a knight starts at the r-th row and c-th column and attempts to make exactly K ...

  5. 【leetcode】688. Knight Probability in Chessboard

    题目如下: On an NxN chessboard, a knight starts at the r-th row and c-th column and attempts to make exa ...

  6. LeetCode——688. Knight Probability in Chessboard

    一.题目链接:https://leetcode.com/problems/knight-probability-in-chessboard/ 二.题目大意: 给定一个N*N的棋盘和一个初始坐标值(r, ...

  7. [LeetCode] Knight Probability in Chessboard 棋盘上骑士的可能性

    On an NxN chessboard, a knight starts at the r-th row and c-th column and attempts to make exactly K ...

  8. [Swift]LeetCode688. “马”在棋盘上的概率 | Knight Probability in Chessboard

    On an NxN chessboard, a knight starts at the r-th row and c-th column and attempts to make exactly K ...

  9. Knight Probability in Chessboard

    2018-07-14 09:57:59 问题描述: 问题求解: 本题本质上是个挺模板的题目.本质是一个求最后每个落点的数目,用总的数目来除有所可能生成的可能性.这种计数的问题可以使用动态规划来进行解决 ...

随机推荐

  1. 转载:python list和set的性能比较+两者转换

    两者性能比较(转自http://www.linuxidc.com/Linux/2012-07/66404.htm) 本来是知道在Python中使用Set是比较高效,但是没想到竟然有这么大的差距: ~$ ...

  2. 查看linux系统CPU及内存配置

    总核数 = 物理CPU个数 X 每颗物理CPU的核数 总逻辑CPU数 = 物理CPU个数 X 每颗物理CPU的核数 X 超线程数 查看物理CPU个数 cat /proc/cpuinfo| grep & ...

  3. 使用tcpdump测试反向代理和lvs的nat区别

    关于反向代理,一个请求过来,实际反向代理服务器要和两个对象做3次握手 客户端到反向代理服务器,是一个3次握手 反向代理服务器请求后端web服务器,是一个3次握手 lvs的nat和反向代理不同. lvs ...

  4. [转]PostgreSQL命令行使用手册

    启动pgsl数据库 1 pg_ctl -D /xx/pgdata start 查看pgsl版本 1 pg_ctl --version 命令行登录数据库 1 psql -U username -d db ...

  5. edit this cookie chrome插件 (HttpAnalyzerStdV3 获取Cookie 后,再用edit this cookie添加cookie)

    插件下载地址及安装方法:http://www.bkill.com/download/154494.html 博客提供下载地址:https://files.cnblogs.com/files/Fooo/ ...

  6. Spark程序运行常见错误解决方法以及优化

    转载自:http://bigdata.51cto.com/art/201704/536499.htm Spark程序运行常见错误解决方法以及优化 task倾斜原因比较多,网络io,cpu,mem都有可 ...

  7. DotNetBar创建的Ribbon、标签式多文档界面

    1.创建一个form作为主窗体,继承自:DevComponents.DotNetBar.RibbonForm 设置属性:IsMdiContainer为true 2.创建一个form,作为子窗体,也继承 ...

  8. springJdbc(jdbcTemplate)事物拦截失效问题解决

    先贴上web.xml和spring-jdbc.xml代码: web.xml代码: <context-param> <param-name>contextConfigLocati ...

  9. Git分支merge和rebase的区别

    Git merge是用来合并两个分支的. git merge b # 将b分支合并到当前分支 同样 git rebase b,也是把 b分支合并到当前分支 原理 如下: 假设你现在基于远程分支&quo ...

  10. Vue Checkbox全选和选中的方法

    <div class="search-content"> <Checkbox :value="checkAll" @click.prevent ...