I have a question about state representation of Q-learning or DQN algorithm. I'm still a beginner of RL, so I'm not sure that is it suitable to take exogenous variables as state features.
For example, in my current project, deciding to charge/discharge an electric vehicle actions according to the real-time fluctuating electricity prices, I'm wondering if the past n-step prices or hours can be considered as state features.
Because both the prices and the hour are just given information in every time step rather than being dependent to the charging/discharging actions, I'm suspicious about whether they can are theoretically qualified to be state features or not.
If they are not qualified, could someone give me a reference or something that I can read?