I'm modeling a problem using Reinforcement Learning (RL). Formally, I have two agents: one of them is the one that I have to program and model, the other one is unpredictable (random). With unpredictable, I mean that I can't even define a set of possible actions for it.
Given that, I thought of modeling the scenario as a single-agent scenario in which the environment changes even without the intervention of my agent. Can I do it?
Reformulating: in RL, should the environment be modified (and then change) only by the agent in a single-agent scenario? Is it possible that even if the agent makes no action the environment changes or should I add some entity (the random agent) to my model?
I tried to find the answer in the book "Reinforcement Learning: An Introduction", 2nd edition, by Sutton and Barto, but I found nothing answering the question in the introductory chapters (1 and 3). With "I found nothing", I mean that the authors neither say that I can do it, nor that I can't.