Stone Game III
Hard · 1-D Dynamic Programming · Explanation and code example
Dynamic Programming (Space Optimized)
How it works
Since each state only depends on the next three states (dp[i+1], dp[i+2], dp[i+3]), we can reduce space from O(n) to O(1) by using a rolling array of size 4. We use modulo arithmetic to cycle through the array indices as we process positions from right to left.
Steps
- Create a small DP array
dp[4]initialized to0. - Iterate from
i = n-1down to0. - For each
i, setdp[i % 4] = negative infinity. Try taking1,2, or3stones, accumulating the total and computingdp[i % 4] = max(dp[i % 4], total - dp[(j + 1) % 4]). - The value
dp[0]represents Alice's advantage. Return "Alice" if positive, "Bob" if negative, "Tie" if zero.
Complexity
- Time complexity:
O(n) - Space complexity:
O(1)extra space.
Things to watch for
Not Handling Negative Stone Values
Unlike other stone game problems, this one allows negative values. Greedily taking the maximum stones does not work because sometimes it is better to take fewer stones to force the opponent into a bad position. Your DP must consider all choices (1, 2, or 3 stones) even when some have negative values.
Returning the Wrong Output Type
The problem asks for a string ("Alice", "Bob", or "Tie"), not a boolean or numeric score. A common mistake is returning the score difference instead of comparing it to determine the winner. Always convert the final score comparison into the correct string result.
Incorrect Base Case Handling
When the index reaches or exceeds the array length, the remaining score is zero. Initializing this incorrectly or not handling the edge case where fewer than 3 stones remain causes out-of-bounds errors or wrong results. Ensure your loop condition properly checks i + X <= n before accessing elements.
Forgetting Both Players Play Optimally
Assuming Bob plays suboptimally (e.g., always takes 1 stone) leads to incorrect results. The DP must model Bob as a rational player who also maximizes his own score. In the score-difference formulation, this is handled by subtracting the opponent's optimal result from the current player's gain.
Python code example
from typing import List
class Solution:
def stoneGameIII(self, stoneValue: List[int]) -> str:
n = len(stoneValue)
dp = [0] * 4
for i in range(n - 1, -1, -1):
total = 0
dp[i % 4] = float("-inf")
for j in range(i, min(i + 3, n)):
total += stoneValue[j]
dp[i % 4] = max(dp[i % 4], total - dp[(j + 1) % 4])
if dp[0] == 0:
return "Tie"
return "Alice" if dp[0] > 0 else "Bob"
C++ code example
class Solution {
public:
string stoneGameIII(vector<int>& stoneValue) {
int n = stoneValue.size();
vector<int> dp(4, 0);
for (int i = n - 1; i >= 0; --i) {
int total = 0;
dp[i % 4] = INT_MIN;
for (int j = i; j < min(i + 3, n); ++j) {
total += stoneValue[j];
dp[i % 4] = max(dp[i % 4], total - dp[(j + 1) % 4]);
}
}
if (dp[0] == 0) return "Tie";
return dp[0] > 0 ? "Alice" : "Bob";
}
};
Source and license
Adapted from NeetCode’s source · MIT license. Node types are supplied by LeetCode where needed.