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 |
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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