What are some examples of greedy and dynamic programming algorithms?

Can you explain the difference between greedy algorithms and dynamic programming?

Sure! Greedy algorithms make the locally optimal choice at each step, hoping to find a global optimum. Dynamic programming, on the other hand, solves problems by breaking them down into simpler subproblems and storing the results to avoid redundant calculations.

Can you give me an example of a problem that can be solved using a greedy algorithm?

Absolutely! A classic example is the Coin Change problem, where you want to make change for a certain amount using the fewest coins possible. A greedy approach would involve always taking the largest denomination coin available.

What about dynamic programming? Can you provide an example?

Certainly! The Fibonacci sequence is a great example. Instead of recalculating Fibonacci numbers multiple times, dynamic programming stores previously calculated values to efficiently compute the next numbers.

How do I decide which approach to use for a specific problem?

It often depends on the problem's structure. If the problem has optimal substructure and overlapping subproblems, dynamic programming is usually the way to go. If it can be solved by making a series of local optimal choices, then a greedy approach might be more suitable.