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Probability of reaching a point with 2 or 3 steps at a time

A person starts walking from position X = 0, find the probability to reach exactly on X = N if she can only take either 2 steps or 3 steps. Probability for step length 2 is given i.e. P, probability for step length 3 is 1 – P.
Examples : 

Input : N = 5, P = 0.20
Output : 0.32
Explanation :-
There are two ways to reach 5.
2+3 with probability = 0.2 * 0.8 = 0.16
3+2 with probability = 0.8 * 0.2 = 0.16
So, total probability = 0.32.

It is a simple dynamic programming problem. It is simple extension of this problem :- count-ofdifferent-ways-express-n-sum-1-3-4
Below is the implementation of the above approach. 

C++




// CPP Program to find probability to
// reach N with P probability to take
// 2 steps (1-P) to take 3 steps
#include <bits/stdc++.h>
using namespace std;
 
// Returns probability to reach N
float find_prob(int N, float P)
{
    double dp[N + 1];
    dp[0] = 1;
    dp[1] = 0;
    dp[2] = P;
    dp[3] = 1 - P;
    for (int i = 4; i <= N; ++i)
        dp[i] = (P)*dp[i - 2] + (1 - P) * dp[i - 3];
 
    return dp[N];
}
 
// Driver code
int main()
{
    int n = 5;
    float p = 0.2;
    cout << find_prob(n, p);
    return 0;
}


Java




// Java Program to find probability to
// reach N with P probability to take
// 2 steps (1-P) to take 3 steps
import java.io.*;
 
class GFG {
     
    // Returns probability to reach N
    static float find_prob(int N, float P)
    {
        double dp[] = new double[N + 1];
        dp[0] = 1;
        dp[1] = 0;
        dp[2] = P;
        dp[3] = 1 - P;
     
        for (int i = 4; i <= N; ++i)
          dp[i] = (P) * dp[i - 2] +
                        (1 - P) * dp[i - 3];
     
        return ((float)(dp[N]));
    }
     
    // Driver code
    public static void main(String args[])
    {
        int n = 5;
        float p = 0.2f;
        System.out.printf("%.2f",find_prob(n, p));
    }
}
 
 
/* This code is contributed by Nikita Tiwari.*/


Python3




# Python 3 Program to find
# probability to reach N with
# P probability to take 2
# steps (1-P) to take 3 steps
 
# Returns probability to reach N
def find_prob(N, P) :
     
    dp =[0] * (n + 1)
    dp[0] = 1
    dp[1] = 0
    dp[2] = P
    dp[3] = 1 - P
     
    for i in range(4, N + 1) :
        dp[i] = (P) * dp[i - 2] + (1 - P) * dp[i - 3]
 
    return dp[N]
 
# Driver code
n = 5
p = 0.2
print(round(find_prob(n, p), 2))
 
# This code is contributed by Nikita Tiwari.


C#




// C# Program to find probability to
// reach N with P probability to take
// 2 steps (1-P) to take 3 steps
using System;
 
class GFG {
     
    // Returns probability to reach N
    static float find_prob(int N, float P)
    {
        double []dp = new double[N + 1];
        dp[0] = 1;
        dp[1] = 0;
        dp[2] = P;
        dp[3] = 1 - P;
     
        for (int i = 4; i <= N; ++i)
        dp[i] = (P) * dp[i - 2] +
                (1 - P) * dp[i - 3];
     
        return ((float)(dp[N]));
    }
     
    // Driver code
    public static void Main()
    {
        int n = 5;
        float p = 0.2f;
        Console.WriteLine(find_prob(n, p));
    }
}
 
 
/* This code is contributed by vt_m.*/


Javascript




<script>
 
// JavaScript Program to find probability to
// reach N with P probability to take
// 2 steps (1-P) to take 3 steps
 
   // Returns probability to reach N
    function find_prob(N, P)
    {
        let dp = [];
        dp[0] = 1;
        dp[1] = 0;
        dp[2] = P;
        dp[3] = 1 - P;
       
        for (let i = 4; i <= N; ++i)
          dp[i] = (P) * dp[i - 2] +
                        (1 - P) * dp[i - 3];
       
        return (dp[N]);
    }
 
// Driver Code
        let n = 5;
        let p = 0.2;
        document.write(find_prob(n, p));
       
      // This code is contributed by chinmoy1997pal.
</script>


PHP




<?php
// PHP Program to find probability to
// reach N with P probability to take
// 2 steps (1-P) to take 3 steps
 
// Returns probability to reach N
function find_prob($N, $P)
{
    $dp;
    $dp[0] = 1;
    $dp[1] = 0;
    $dp[2] = $P;
    $dp[3] = 1 - $P;
    for ($i = 4; $i <= $N; ++$i)
        $dp[$i] = ($P) * $dp[$i - 2] +
                  (1 - $P) * $dp[$i - 3];
 
    return $dp[$N];
}
 
// Driver code
$n = 5;
$p = 0.2;
echo find_prob($n, $p);
 
// This code is contributed by mits.
?>


Output

0.32

Time Complexity: O(n)
Auxiliary Space: O(n)
 Efficient approach: Space optimization O(1)

In the previous approach, the current value dp[i] only depends on the previous 2 values of dp i.e. dp[i-2] and dp[i-3]. So to optimize the space complexity we can store the previous 4 values of Dp in 4 variables  his way, the space complexity will be reduced from O(N) to O(1)

Implementation Steps:

  • Initialize variables for dp[0], dp[1], dp[2], and dp[3] as 1, 0, P, and 1-P respectively.
  • Iterate from i = 4 to N and use the formula dp[i] = (P)*dp[i – 2] + (1 – P) * dp[i – 3] to compute the current value of dp.
  • After each iteration, update the values of dp0, dp1, dp2, and dp3 to dp1, dp2, dp3, and curr respectively.
  • Return the final value of curr.

Implementation:

C++




// CPP Program to find probability to
// reach N with P probability to take
// 2 steps (1-P) to take 3 steps
#include <bits/stdc++.h>
using namespace std;
 
// Returns probability to reach N
float find_prob(int N, float P)
{   
      // to store current value
    double curr;
     
      // store previous 4 values of DP
    double dp0 = 1, dp1=0, dp2=P, dp3= 1-P;
     
      // iterate over subproblems to get
      // current solution from previous computations
    for (int i = 4; i <= N; ++i){
        curr = (P)*dp2 + (1 - P) * dp1;
       
          // assigning values to iterate further
        dp0=dp1;
        dp1=dp2;
        dp2=dp3;
        dp3=curr;
    }
     
      // return final answer
    return curr;
}
 
// Driver code
int main()
{
    int n = 5;
    float p = 0.2;
    cout << find_prob(n, p);
    return 0;
}


Java




import java.util.*;
 
public class Main {
 
    // Returns probability to reach N
    static float find_prob(int N, float P) {
 
        // to store current value
        double curr;
 
        // store previous 4 values of DP
        double dp0 = 1, dp1 = 0, dp2 = P, dp3 = 1 - P;
 
        // iterate over subproblems to get
        // current solution from previous computations
        for (int i = 4; i <= N; ++i) {
            curr = (P) * dp2 + (1 - P) * dp1;
 
            // assigning values to iterate further
            dp0 = dp1;
            dp1 = dp2;
            dp2 = dp3;
            dp3 = curr;
        }
 
        // return final answer
        return (float) curr;
    }
 
    // Driver code
    public static void main(String[] args) {
        int n = 5;
        float p = 0.2f;
        System.out.println(find_prob(n, p));
    }
}


Python3




# Function to find the probability to reach N with P probability to
# take 2 steps and (1-P) to take 3 steps
def find_prob(N, P):
    # Initialize variables to store current and previous values
    curr = 0.0
 
    # Initialize previous 4 values of DP
    dp0, dp1, dp2, dp3 = 1.0, 0.0, P, 1 - P
 
    # Iterate over subproblems to calculate the
    # current solution from previous computations
    for i in range(4, N + 1):
        curr = P * dp2 + (1 - P) * dp1
 
        # Update values for the next iteration
        dp0, dp1, dp2, dp3 = dp1, dp2, dp3, curr
 
    # Round the final answer to 2 decimal places
    return round(curr, 2)
 
# Driver code
if __name__ == "__main__":
    n = 5
    p = 0.2
    print(find_prob(n, p))


Javascript




// Returns probability to reach N
function find_prob(N, P) {   
  // to store current value
  let curr;
   
  // store previous 4 values of DP
  let dp0 = 1, dp1 = 0, dp2 = P, dp3 = 1 - P;
   
  // iterate over subproblems to get
  // current solution from previous computations
  for (let i = 4; i <= N; ++i) {
    curr = (P * dp2) + ((1 - P) * dp1);
     
    // assigning values to iterate further
    dp0 = dp1;
    dp1 = dp2;
    dp2 = dp3;
    dp3 = curr;
  }
   
  // return final answer
  return curr;
}
 
// Driver code
let n = 5;
let p = 0.2;
console.log(find_prob(n, p).toFixed(2));


Output

0.32

Time complexity: O(N)
Auxiliary Space: O(1)

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