The trick is to provide dense rewards, i.e. not only once full goal is reached, but a little bit for every random flailing of the agent in the approximately correct direction.
(Actually, "pretty hard to justify" might be understating it. How can we confidently extract any signal from a failure to solve a problem if we don't even know if the problem is solvable?)
> How can we confidently extract any signal from a failure to solve a problem if we don't even know if the problem is solvable?)
You rule out all the stuff that doesn’t work.
Yes this is difficult and usually very costly. Credit assignment is a deep problem. But if you didn’t find yourself in a hard mode situation, you wouldn’t be using RL.