w

Stochastic matrix - Wikipedia  https://en.wikipedia.org/wiki/Stochastic_matrix

Suppose you have a timer and a row of five adjacent boxes, with a cat in the first box and a mouse in the fifth box at time zero. The cat and the mouse both jump to a random adjacent box when the timer advances. E.g. if the cat is in the second box and the mouse in the fourth one, the probability is one fourth that the cat will be in the first box and the mouse in the fifth after the timer advances. If the cat is in the first box and the mouse in the fifth one, the probability is one that the cat will be in box two and the mouse will be in box four after the timer advances. The cat eats the mouse if both end up in the same box, at which time the game ends. The random variable K gives the number of time steps the mouse stays in the game.

The Markov chain that represents this game contains the following five states specified by the combination of positions (cat,mouse). Note that while a naive enumeration of states would list 25 states, many are impossible either because the mouse can never have a lower index than the cat (as that would mean the mouse occupied the cat's box and survived to move past it), or because the sum of the two indices will always have even parity. In addition, the 3 possible states that lead to the mouse's death are combined into one:

  • State 1: (1,3)
  • State 2: (1,5)
  • State 3: (2,4)
  • State 4: (3,5)
  • State 5: game over: (2,2), (3,3) & (4,4).
 

stochastic matrix的更多相关文章

  1. 随机矩阵(stochastic matrix)

          最近一个月来一直在看Google排序的核心算法---PageRank排序算法[1][2],在多篇论文中涉及到图论.马尔可夫链的相关性质说明与应用[3][4][5],而最为关键,一直让我迷惑 ...

  2. 【十大经典数据挖掘算法】PageRank

    [十大经典数据挖掘算法]系列 C4.5 K-Means SVM Apriori EM PageRank AdaBoost kNN Naïve Bayes CART 我特地把PageRank作为[十大经 ...

  3. PageRank算法初探

    1. PageRank的由来和发展历史 0x1:源自搜索引擎的需求 Google早已成为全球最成功的互联网搜索引擎,在Google出现之前,曾出现过许多通用或专业领域搜索引擎.Google最终能击败所 ...

  4. pagerank 数学基础

    网页排序的任务中,最核心的难点在于判别网页质量. 将互联网上的网页模拟为一个节点,而这个网页的“出链”看做是指向其他节点的一条“有向边”,而“入链”则是其他节点指向这个节点的有向边.这样整个网络就变成 ...

  5. (zhuan) Deep Deterministic Policy Gradients in TensorFlow

          Deep Deterministic Policy Gradients in TensorFlow AUG 21, 2016 This blog from: http://pemami49 ...

  6. HDOJ 题目5097 Page Rank(矩阵运算,模拟)

    Page Rank Time Limit: 3000/1500 MS (Java/Others)    Memory Limit: 100000/100000 K (Java/Others) Tota ...

  7. Spark MLlib LDA 源代码解析

    1.Spark MLlib LDA源代码解析 http://blog.csdn.net/sunbow0 Spark MLlib LDA 应该算是比較难理解的,当中涉及到大量的概率与统计的相关知识,并且 ...

  8. MATLAB实例:对称双随机矩阵

    MATLAB实例:对称双随机矩阵 作者:凯鲁嘎吉 - 博客园 http://www.cnblogs.com/kailugaji/ 双随机矩阵(doubly stochastic matrix):元素属 ...

  9. KDD2016,Accepted Papers

    RESEARCH TRACK PAPERS - ORAL Title & Authors NetCycle: Collective Evolution Inference in Heterog ...

随机推荐

  1. pthread_barrier_init,pthread_barrier_wait简介(转)

    pthread_barrier 系列函数在<pthread.h>中定义,用于多线程的同步,它包含三个函数: --pthread_barrier_init() --pthread_barri ...

  2. React Native :加载新闻列表

    代码地址如下:http://www.demodashi.com/demo/13212.html 标签与内容页联动 上一节(React Native : 自定义视图)做到了点击标签自动移动,还差跟下面的 ...

  3. CStdioFile类学习笔记<转>

    本文转自:http://www.cnblogs.com/JiMuStudio/archive/2011/07/17/2108496.html   CStdioFile类的声明保存再afx.h头文件中. ...

  4. Python 的错误和异常处理

    语法错误 Python 的语法错误或者称之为解析错,如下: >>> while True print('Hello world') File "<stdin>& ...

  5. select/poll/epoll原理探究及总结

    select,poll,epoll都是IO多路复用的机制.I/O多路复用就通过一种机制,可以监视多个描述符,一旦某个描述符就绪(一般是读就绪或者写就绪),能够通知程序进行相应的读写操作.但select ...

  6. 设置U盘启动

    利用快捷键来设置U盘启动,利用快捷键启动相对来说比较简单快捷,推荐大家使用(重要提醒:选择热键前,请先插入U盘) 组装机主板 品牌笔记本 品牌台式机 主板品牌 启动按键 笔记本品牌 启动按键 台式机品 ...

  7. 应用phpexcel导出excel文件后打不开的问题解决方法

    应用phpexcel导出excel文件后打不开,提示“文件格式或文件扩展名无效,请确定文件未损坏,并且文件扩展名与文件的格式匹配”. 试了以下方法: 1.首先区分文件格式是2003,还是2007. 参 ...

  8. CenterOS卸载和安装MYSQL

    1.首先在命令行输入mysql,看一下本地计算机上是否有mysql. 2.卸载mysql服务: 首先查看安装的rpm的包:rpm –qa |grep mysql    对之前的服务进行删除.rpm – ...

  9. python模块学习之re

    正则表达式本质就是表示某种规则的一串字符. 匹配的规则叫做模式(pattern),模式作用于对象. 模式和对象可以是Unicode或者字节,但是,不能够混用,比如:模式为Unicode,对象为字节,像 ...

  10. FineReport实现java报表多级上报的效果图

    Java报表-上报流程管理 Java报表-上报任务管理 Java报表-我的上报任务 Java报表-系统说明