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Maximize the number of coins collected by X, assuming Y also plays optimally

Two players X and Y are playing a game in which there are pots of gold arranged in a line, each containing some gold coins. They get alternating turns in which the player can pick a pot from one of the ends of the line. The winner is the player who has a higher number of coins at the end. The objective is to maximize the number of coins collected by X, assuming Y also plays optimally. Return the maximum coins X could get while playing the game. Initially, X starts the game.

Examples:

Input: N = 4, Q[] = {8, 15, 3, 7}
Output: 22
Explanation: Player X starts and picks 7. Player Y picks the pot containing 8. Player X picks the pot containing 15. Player Y picks 3. Total coins collected by X = 7 + 15 = 22.

Input:N = 4, A[] = {2, 2, 2, 2}
Output: 4 

Approach: This can be solved with the following idea:

Using Dynamic programming as it has an optimum substructure and overlapping subproblems.

Steps involved in the implementation of code:

  • Declare a static 1002 x 1002 2D integer array with the name dp.
  • Add a public static method called “getMaxCoins” that accepts an integer array called “coins, ” together with the parameters “integer start” and “integer end, ” and returns an integer result.
  • Return zero if start exceeds finish.                                                                                                                                         
  • Return dp[start][end] if dp[start][end] is not equal to -1.
  • Create the variables option1 and option2 as two integers.
  • GetMaxCoins with parameters coins, start+1, end-1, and getMaxCoins with parameters coins, start, end-2 are called recursively with the option1 set to coins[end] plus the minimum value in between.
  • Option 2 should be set to coins[start] plus the minimum value in between calls to the recursive functions getMaxCoins with the arguments coins, start+2, end, and getMaxCoins with the arguments coins, start+1, end-1.                                      
  • Set the highest value possible between options 1 and 2 for dp[start][end].
    • Bring back dp[start][end].
  • Make a public static method called maxCoins that receives an integer value as a return parameter and accepts integer array coins and an integer n as input arguments.
  • To add -1 values to the dp array, use a nested loop.
  • Return the value of the getMaxCoins method with parameters coins, 0, n-1

Below is the code implementation of the above approach:

C++14




// C++ code of the above approach
#include <bits/stdc++.h>
using namespace std;
 
int dp[1002][1002];
 
// Returns the maximum coins that
// can be collected from start to end
int getMaxCoins(int coins[], int start, int end)
{
    // Base case: When start index is
    // greater than end index
    if (start > end) {
        return 0;
    }
 
    // If we have already computed the
    // solution for this sub-problem
    if (dp[start][end] != -1) {
        return dp[start][end];
    }
 
    // Case 1: Choose the last coin,
    // then we can choose between the
    // first and second-last coins
    int option1
        = coins[end]
          + min(getMaxCoins(coins, start + 1, end - 1),
                getMaxCoins(coins, start, end - 2));
 
    // Case 2: Choose the first coin,
    // then we can choose between the
    // second and last coins
    int option2
        = coins[start]
          + min(getMaxCoins(coins, start + 2, end),
                getMaxCoins(coins, start + 1, end - 1));
 
    // Store the maximum coins that
    // can be collected from start
    // to end
    dp[start][end] = max(option1, option2);
 
    return dp[start][end];
}
 
int maxCoins(int coins[], int n)
{
    // Initialize the DP array with -1
    memset(dp, -1, sizeof(dp));
 
    return getMaxCoins(coins, 0, n - 1);
}
 
// Driver code
int main()
{
    int coins[] = { 8, 15, 3, 7 };
    int n = sizeof(coins) / sizeof(coins[0]);
    int maxCoin = maxCoins(coins, n);
 
    // Function call
    cout << maxCoin << endl;
 
    return 0;
}


Java




// Java code of the above approach
import java.util.*;
 
class GfG {
    public static int dp[][] = new int[1002][1002];
 
    // Returns the maximum coins that
    // can be collected from start to end
    public static int getMaxCoins(int[] coins, int start,
                                  int end)
    {
 
        // Base case: When start index is
        // greater than end index
        if (start > end) {
            return 0;
        }
 
        // If we have already computed the
        // solution for this sub-problem
        if (dp[start][end] != -1) {
            return dp[start][end];
        }
 
        // Case 1: Choose the last coin,
        // then we can choose between the
        // first and second-last coins
        int option1
            = coins[end]
              + Math.min(
                    getMaxCoins(coins, start + 1, end - 1),
                    getMaxCoins(coins, start, end - 2));
 
        // Case 2: Choose the first coin,
        // then we can choose between the
        // second and last coins
        int option2
            = coins[start]
              + Math.min(
                    getMaxCoins(coins, start + 2, end),
                    getMaxCoins(coins, start + 1, end - 1));
 
        // Store the maximum coins that
        // can be collected from start
        // to end
        dp[start][end] = Math.max(option1, option2);
 
        return dp[start][end];
    }
 
    public static int maxCoins(int[] coins, int n)
    {
 
        // Initialize the DP array with -1
        for (int i = 0; i < 1001; i++) {
            Arrays.fill(dp[i], -1);
        }
 
        return getMaxCoins(coins, 0, n - 1);
    }
 
    // Driver code
    public static void main(String args[])
    {
        int[] coins = { 8, 15, 3, 7 };
        int n = coins.length;
        int maxCoins = maxCoins(coins, n);
 
        // Function call
        System.out.println(maxCoins);
    }
}


Python3




class GfG:
    dp = [[-1 for i in range(1002)] for j in range(1002)]
 
    # Returns the maximum coins that
    # can be collected from start to end
    def getMaxCoins(self, coins, start, end):
        # Base case: When start index is
        # greater than end index
        if start > end:
            return 0
 
        # If we have already computed the
        # solution for this sub-problem
        if self.dp[start][end] != -1:
            return self.dp[start][end]
 
        # Case 1: Choose the last coin,
        # then we can choose between the
        # first and second-last coins
        option1 = coins[end] + min(self.getMaxCoins(coins, start + 1, end - 1), self.getMaxCoins(coins, start, end - 2))
 
        # Case 2: Choose the first coin,
        # then we can choose between the
        # second and last coins
        option2 = coins[start] + min(self.getMaxCoins(coins, start + 2, end), self.getMaxCoins(coins, start + 1, end - 1))
 
        # Store the maximum coins that
        # can be collected from start
        # to end
        self.dp[start][end] = max(option1, option2)
 
        return self.dp[start][end]
 
    def maxCoins(self, coins, n):
        # Initialize the DP array with -1
        for i in range(1001):
            for j in range(1001):
                self.dp[i][j] = -1
 
        return self.getMaxCoins(coins, 0, n - 1)
 
# Driver code
if __name__ == '__main__':
    coins = [8, 15, 3, 7]
    n = len(coins)
    gfg = GfG()
    maxCoins = gfg.maxCoins(coins, n)
 
    # Function call
    print(maxCoins)


C#




using System;
 
class GFG {
    public static int[,] dp = new int[1002, 1002];
 
    // Returns the maximum coins that can be collected from start to end
    public static int getMaxCoins(int[] coins, int start, int end) {
        // Base case: When start index is greater than end index
        if (start > end) {
            return 0;
        }
 
        // If we have already computed the solution for this sub-problem
        if (dp[start, end] != -1) {
            return dp[start, end];
        }
 
        // Case 1: Choose the last coin, then we can choose
       // between the first and second-last coins
        int option1 =
          coins[end] + Math.Min(getMaxCoins(coins, start + 1, end - 1),
                                getMaxCoins(coins, start, end - 2));
 
        // Case 2: Choose the first coin,
       // then we can choose between the second and last coins
        int option2 =
          coins[start] + Math.Min(getMaxCoins(coins, start + 2, end),
                                  getMaxCoins(coins, start + 1, end - 1));
 
        // Store the maximum coins that can be collected from start to end
        dp[start, end] = Math.Max(option1, option2);
 
        return dp[start, end];
    }
 
    public static int maxCoins(int[] coins, int n) {
        // Initialize the DP array with -1
        for (int i = 0; i < 1001; i++) {
            for (int j = 0; j < 1001; j++) {
                dp[i,j] = -1;
            }
        }
 
        return getMaxCoins(coins, 0, n - 1);
    }
 
    // Driver code
    public static void Main() {
        int[] coins = {8, 15, 3, 7};
        int n = coins.Length;
        int mxCoins = maxCoins(coins, n);
 
        // Function call
        Console.WriteLine(mxCoins);
    }
}


Javascript




// JavaScript code of the above approach
 
// Returns the maximum coins that
// can be collected from start to end
function getMaxCoins(coins, start, end, dp) {
     
    // Base case: When start index is
    // greater than end index
    if (start > end) {
        return 0;
    }
 
    // If we have already computed the
    // solution for this sub-problem
    if (dp[start][end] != -1) {
        return dp[start][end];
    }
 
    // Case 1: Choose the last coin,
    // then we can choose between the
    // first and second-last coins
    let option1 =
        coins[end]
        + Math.min(getMaxCoins(coins, start + 1, end - 1, dp),
                    getMaxCoins(coins, start, end - 2, dp));
 
    // Case 2: Choose the first coin,
    // then we can choose between the
    // second and last coins
    let option2 =
        coins[start]
        + Math.min(getMaxCoins(coins, start + 2, end, dp),
                    getMaxCoins(coins, start + 1, end - 1, dp));
 
    // Store the maximum coins that
    // can be collected from start
    // to end
    dp[start][end] = Math.max(option1, option2);
 
    return dp[start][end];
}
 
function maxCoins(coins, n) {
    let dp = [];
 
    // Initialize the DP array with -1
    for (let i = 0; i <= n; i++) {
        dp[i] = Array(n).fill(-1);
    }
 
    return getMaxCoins(coins, 0, n - 1, dp);
}
 
// Driver code
let coins = [ 8, 15, 3, 7 ];
let n = coins.length;
let maxCoin = maxCoins(coins, n);
 
// Function call
console.log(maxCoin);
// This code is contributed by prasad264


Output

22



Time Complexity: O(N2)
Auxiliary Space: O(N2)

Efficient approach : Using DP Tabulation method ( Iterative approach )

The approach to solve this problem is same but DP tabulation(bottom-up) method is better then Dp + memoization(top-down) because memoization method needs extra stack space of recursion calls.

Steps to solve this problem :

  • Create a DP of size n*n to store the solution of the subproblems .
  • Now Iterate over subproblems to get the value of current problem form previous computation of subproblems stored in DP
  • Return the final solution stored in dp[0][n – 1].

Implementation :

C++




// C++ code of the above approach
#include <bits/stdc++.h>
using namespace std;
 
// Returns the maximum coins that
// can be collected from start to end
int maxCoins(int coins[], int n) {
    // Base case
    if (n == 0)
        return 0;
         
    //intialize dp
    int dp[n][n];
     
    //iterate over subproblems
    for (int len = 1; len <= n; len++) {
        for (int start = 0; start <= n - len; start++) {
            int end = start + len - 1;
            int x = ((start + 2 <= end) ? dp[start + 2][end] : 0);
            int y = ((start + 1 <= end - 1) ? dp[start + 1][end - 1] : 0);
            int z = ((start <= end - 2) ? dp[start][end - 2] : 0);
             
            //current value
            dp[start][end] = max(coins[start] + min(x, y), coins[end] + min(y, z));
        }
    }
     
    //return answer
    return dp[0][n - 1];
}
 
//Driver Code
int main() {   
    int coins[] = { 8, 15, 3, 7 };
    int n = sizeof(coins) / sizeof(coins[0]);
    int maxCoin = maxCoins(coins, n);
 
    cout << maxCoin << endl;
 
    return 0;
}


Python3




# Python code of the above approach
def maxCoins(coins, n):
    # Base case
    if n == 0:
        return 0
     
    # intialize dp
    dp = [[0 for j in range(n)] for i in range(n)]
     
    # iterate over subproblems
    for length in range(1, n+1):
        for start in range(n - length + 1):
            end = start + length - 1
            x = dp[start + 2][end] if start + 2 <= end else 0
            y = dp[start + 1][end - 1] if start + 1 <= end - 1 else 0
            z = dp[start][end - 2] if start <= end - 2 else 0
             
            # current value
            dp[start][end] = max(coins[start] + min(x, y), coins[end] + min(y, z))
     
    # return answer
    return dp[0][n - 1]
 
# Driver Code
coins = [8, 15, 3, 7]
n = len(coins)
maxCoin = maxCoins(coins, n)
 
print(maxCoin)
 
# This code is contributed by Sakshi


Output

22

Time Complexity: O(N^2)

Auxiliary Space: O(N^2)

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Dominic Rubhabha-Wardslaus
Dominic Rubhabha-Wardslaushttp://wardslaus.com
infosec,malicious & dos attacks generator, boot rom exploit philanthropist , wild hacker , game developer,
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