In that case, the first 0.9s of random guessing was useful and didn't generate workload.

If you had to find the solution by hand, random guessing is probably not the optimal way.

Here, M mode implies exposure knowledge and semi-auto modes reduce the exposure workload to EC.

Stochastic optimization methods generalize deterministic methods for deterministic problems.

I don't understand this. Where is the connection between random variables and deterministic, anything?