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I think the dynamic programming meant here is more general. They mean saving results of a recursively formulated algorithm in a table so that you don't have to recompute them. This can be used for example for finding longest common subsequences, but it is much more general.

Can you elaborate on the general search procedure?

Is there a good resource that ties algorithms together like you've done here, but less concise?

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they do mean dynamic programming in a more general sense: but dynamic programming was invented originally to solve Bellman's equation. it turns out many other problems have a similar structure which is quite surprising! before bellman's seminal work in 1940s, it wasn't known how to efficiently these problems. indeed, you can often do something like Q-learning for finding approximate solutions to dynamic programming problems even faster.

the general search procedure is just A* search but with the beam search pruning each time you expand the fringe of exploration.

i don't know a good source, i picked this up from a bunch of courses/research.

Thanks! You should consider writing an article about this :)

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