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First, pair up each player's score and age, and then sort them based on age and score. This allows us to always build teams that do not violate the conflict rule of younger players having higher scores than older players. Subsequently, use dynamic programming to build the optimal solution progressively by calculating the best team score achievable up to this player, considering current player's score only if it resolves no conflicts by adhering to the sorted order.
Time Complexity: O(n^2), where n is the number of players.
Space Complexity: O(n) for the DP array.
1function bestTeamScore(scores, ages) {
2 const players = scores.map((score, i) => [ages[i], score]);
3 players.sort(([age1, score1], [age2, score2]) => age1 - age2 || score1 - score2);
4
5 const dp = Array(scores.length).fill(0);
6 let maxScore = 0;
7
8 for (let i = 0; i < scores.length; i++) {
9 dp[i] = players[i][1];
10 for (let j = 0; j < i; j++) {
11 if (players[j][1] <= players[i][1]) {
12 dp[i] = Math.max(dp[i], dp[j] + players[i][1]);
13 }
14 }
15 maxScore = Math.max(maxScore, dp[i]);
16 }
17
18 return maxScore;
19}Shows method to apply sorting by age and score in JavaScript, followed by dynamic programming to calculate maximum team scores without any conflicts.