In short
An algorithmic approach that makes the locally optimal choice at each step, hoping (and sometimes provably) it leads to a globally optimal solution.
How to learn this
- 1Solve a classic greedy problem: activity selection or coin change (with certain coin sets).
- 2Learn to recognize when greedy actually works vs when it gives a wrong answer.
- 3Compare a greedy solution to a DP solution for the same problem when greedy fails.
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