Am I understanding this correctly that dynamic programming == breaking a problem into smaller (reoccurring) sub-problems and using caching to improve performance?
It's slightly more nuanced than that, but you've got the basic idea.
The caching is kind of mandatory as the sub-problems interact.
That is conceptually how dynamic programming works, but in practice the way you build the cache is from the bottom up rather than from the top down. It's a bit like how you can implement computation of the Fibonacci sequence in a top-down manner using a recursive function with caching, but it is a lot more efficient to instead build it in a bottom-up manner.
Am I understanding this correctly that dynamic programming == breaking a problem into smaller (reoccurring) sub-problems and using caching to improve performance?
It's slightly more nuanced than that, but you've got the basic idea.
The caching is kind of mandatory as the sub-problems interact.
That is conceptually how dynamic programming works, but in practice the way you build the cache is from the bottom up rather than from the top down. It's a bit like how you can implement computation of the Fibonacci sequence in a top-down manner using a recursive function with caching, but it is a lot more efficient to instead build it in a bottom-up manner.