Optimization

Optimization

Dynamic programming.

Dynamic programming is a powerful algorithmic design paradigm. The key idea is to save state to avoid recomputation: break a large computational problem up into smaller subproblems, store the answers to those smaller subproblems, and, eventually, use the stored answers to solve the original problem. This avoids recomputing the same quantity over and over again, and a potential exponential blow-up in the running time. We now consider two examples.

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