When should I use dynamic programming?

What is dynamic programming and when should I use it?

Dynamic programming is a method for solving complex problems by breaking them down into simpler subproblems. You should use it when a problem can be divided into overlapping subproblems that can be solved independently.

Can you give me an example of a problem that can be solved using dynamic programming?

Sure! A classic example is the Fibonacci sequence. Instead of recalculating Fibonacci numbers multiple times, dynamic programming allows you to store previously calculated values to optimize the process.

Are there any specific scenarios where dynamic programming is particularly useful?

Yes, dynamic programming is particularly useful in optimization problems, such as the knapsack problem, shortest path problems, and in algorithms like the longest common subsequence.

How do I know if a problem is suitable for dynamic programming?

Look for problems that exhibit overlapping subproblems and optimal substructure. If you can break the problem down and reuse solutions to subproblems, dynamic programming is likely a good fit.