It depends on whether you are implementing a library to support RL or using one that does - in the former case, yah, you better have a grip, in the latter, you need to understand enough to know how to utilize the library and not feed it nasty things.... this isn't to say you can be mathematically illiterate, however there are levels to required knowledge - the same as you don't need to know how to make a compiler to use one
I agree to an extend. The current state of RL algorithms are more fragmented and have limited application comparing to something like a CNN.
So unless one only wants to learn how to play Atari, they won't be able to "fix" an algorithm if it breaks down in an untested environment. E.g. a non deterministic sparse reward game.
If one day there is a generalized algorithm that can solve large set of RL problems, then I think a high level intuition is probably enough to use RL, but for now, I'd say RL is definitely not for the faint of heart.
True - I often make the heretical argument that SL vs RL is just a question of where the labeling comes from :-) You are correct that the tooling is weaker in this space, but it is growing - my point is only that there's a difference between knowing how to use the tool and knowing how to make the tool - making the tool can liquify your brain -- using someone else's tool (assuming its a good tool) will simply give you headaches from time to time :-D
