Question 1

What is the main difference between Greedy Algorithms and Dynamic Programming?

Accepted Answer

The main difference is that Greedy Algorithms make a locally optimal choice at each step with the hope of finding a global optimum, without reconsidering past choices. Dynamic Programming, on the other hand, makes decisions based on the results of subproblems, and may reconsider choices to find the global optimum.

Question 2

When does a greedy approach fail?

Accepted Answer

A greedy approach fails when a locally optimal choice does not lead to a globally optimal solution. For example, in the 0/1 Knapsack problem, a greedy approach of picking the most valuable items first might not be optimal if those items are also very heavy, leaving no space for other valuable items. Dynamic Programming is required to solve this problem optimally.

Greedy Algorithms vs. Dynamic Programming

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