Search⌘ K
AI Features
Home
Courses
Grokking the Coding Interview Patterns in Python

Solution: Maximum Points After Enemy Battles

Explore how to use greedy algorithms to solve an optimization problem that involves defeating enemies with varying energy costs. Understand the strategy to accumulate maximum points by prioritizing the weakest enemy and absorbing others’ energy. This lesson offers a clear approach to efficiently solving similar problems.

We'll cover the following...

Statement

You are given an integer array enemyEnergies where each element represents the energy value of an enemy, and an integer currentEnergy representing your initial energy.

You start with 00 points, and all enemies are initially unmarked. You may perform either of the following operations any number of times to accumulate points:

Operation 1 — Choose an unmarked enemy i such that currentEnergy >= enemyEnergies[i]:

  • Your points increase by 11.

  • Your energy decreases: currentEnergy = currentEnergy - enemyEnergies[i].

Operation 2 — If you have at least 11 point, choose any unmarked enemy i:

  • Your energy increases: currentEnergy = currentEnergy + enemyEnergies[i].

  • Enemy i becomes marked.

Return the maximum number of points you can achieve by performing these operations optimally.

Constraints:

  • 1≤1 \leq enemyEnergies.length ...