I see the motivation as given practical compute limits, it may be much easier to have the system find an action the overseer approves of instead of imitating the overseer directly. Using RL also allows you to use any advances that are made in RL by the machine learning community to try to remain competitive.
I see the motivation as given practical compute limits, it may be much easier to have the system find an action the overseer approves of instead of imitating the overseer directly. Using RL also allows you to use any advances that are made in RL by the machine learning community to try to remain competitive.