The conversation between human and AI assistant.
What are the differences between dynamic programming and greedy?
Can you give an example of when dynamic programming would be a better approach than greedy?
Sure, let's say you have to traverse a grid with obstacles from the top left corner to the bottom right corner, with the goal of reaching the destination with the minimum number of steps. In this case, dynamic programming would be a better approach as it involves breaking down the problem into smaller subproblems, while also keeping track of previously computed subproblems to avoid redundant computations. Greedy algorithms may not always yield the optimal solution in this case.