[whatever1]

Yeah I don't buy the baseline comparison of the "expert designed controller" that cannot stay within bounds.

We can control systems that have not only fluid-mechanical, but also heat transfer and chemical reactions, all happening at the same time with huge bars of uncertainty.

Next.

[krisoft]

The environment has been released. If you or anyone else wishes to give it a go you can develop a controller any whichever way you fancy.

The baseline comparison is not meant to be some final word on any given controller. In this case they clearly cite it to a particular paper. [1]

1: https://github.com/google/balloon-learning-environment/blob/...

[whatever1]

Then their wording is misleading.

They compared against another bad RL system and they are better than that.

That is far from an "expert control system"

[krisoft]

Ah! I see where the miscommunication happens. They use the word in a particular context.

Here "expert control system" means that it has a decision logic designed by some humans. They sit down wrote an algorithm and said "I think this is a good idea based on what I know about the problem." Compare it with a reinforcement learning system, where they let loose a generic learning algorithm on the problem and then they see how it performs.

In this context "expert control system" doesn't mean that it was expertly designed, or even that it is any good. It just means that humans designed it for this particular problem.

[whatever1]

This makes sense. Thanks for the clarification :)

[mockery]

The word expert is not being used in the colloquial sense, but in the technical sense of an "Expert System": https://en.wikipedia.org/wiki/Expert_system

[scandido]

Between prevailing winds, power and superpressure limitations, etc., it is often the case that a balloon cannot be regulated within bounds regardless of the quality of controller. Nonetheless I’m certain there are better control laws than this solution.