Here we will see one matrix probability problem. We have one rectangular matrix. We can move four directions from the current cell with equal probability. These four directions are left, right, up and down. We have to calculate the probability after N moves from position M[i, j].
Here we will do something related to DFS. We will traverse recursively traverse in each of the four possible rooms from the current room. Then we will calculate the probability with one less move. As each of the four directions has equal probability, then each direction will contribute 0.25 of total probability. If we cross the matrix boundary, we will return 0, and 1 will be returned when N move is completed. Let us see the algorithm to get the idea.
Algorithm
matProb(m, n, x, y, N)
Begin if x,y is not in matrix boundary m, n, then return 0 if N is 0 , then return 1 prob := 0 prob := prob + matProb(m, n, x-1, y, N-1) * 0.25 prob := prob + matProb(m, n, x+1, y, N-1) * 0.25 prob := prob + matProb(m, n, x, y+1, N-1) * 0.25 prob := prob + matProb(m, n, x, y-1, N-1) * 0.25 return prob End
Example
#include<iostream>
using namespace std;
bool isSafe(int x, int y, int m, int n) { //function to check whether (x,y)
is in matrix or not
if(x >= 0 && x < m && y >= 0 && y < n){
return true;
}
return false;
}
double matProb(int m, int n, int x, int y, int N) {
if (!isSafe(x, y, m, n)) //if coundary is crossed
return 0.0;
if (N == 0) //when N is 0, or N is completed, return 1
return 1.0;
double probability = 0.0;
probability += matProb(m, n, x - 1, y, N - 1) * 0.25; //move left
probability += matProb(m, n, x, y + 1, N - 1) * 0.25; //move up
probability += matProb(m, n, x + 1, y, N - 1) * 0.25; //move right
probability += matProb(m, n, x, y - 1, N - 1) * 0.25; //move down
return probability;
}
int main() {
int m = 7, n = 8;
int x = 1, y = 1;
int N = 4;
cout << "Matrix Probability is " << matProb(m, n, x, y, N);
}Output
Matrix Probability is 0.664062