I was reading this article about the question "Why do we dream?" in which the author discusses dreams as a form of rehearsal for future threats, and presents it as an evolutive advantage. My question is whether this idea has been explored in the context of RL.
For example, in a competition between AIs on a shooter game, one could design an agent that, besides the behavior it has learned in a "normal" training, seeks for time in which is out of danger, to then use its computation time in the game to produce simulations that would further optimize its behavior. As the agent still needs to be somewhat aware of its environment, it could alternate between processing the environment and this kind of simulation. Note that this "in-game" simulation has an advantage with respect to the "pre-game" simulations used for training; the agent in the game experiences the behavior of the other agents, which could not have been predicted beforehand, and then simulates on top of these experiences, e.g. by slightly modifying them.
For more experienced folks, does this idea make sense? has something similar been explored?
I have absolutely no experience in the field, so I apologize if this question is poorly worded, dumb or obvious. I would appreciate suggestions on how to improve it if this is the case.