What is the difference between greedy algorithms and dynamic programming?
An example of an AI chatbot conversation about greedy vs dynamic programming algorithms.
What is the difference between greedy algorithms and dynamic programming?
Greedy algorithms make the locally optimal choice at each stage, while dynamic programming solves problems by breaking them down into simpler subproblems and storing their solutions.
Can you give me an example of a problem that uses dynamic programming?
Sure! The Fibonacci sequence is a classic example. Instead of recalculating Fibonacci numbers, dynamic programming stores previously computed values.
And what about a problem that uses a greedy algorithm?
A common example is the coin change problem, where you want to make change for a certain amount using the fewest coins possible.
When should I use one approach over the other?
Use greedy algorithms when local optimization leads to a global solution, and dynamic programming when the problem has overlapping subproblems and optimal substructure.
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