r/MachineLearning - [R] Reinforcement Learning in Non-Stationary Environments

I don't think this is as significant of a problem as you think it is. If I understood the paper correctly, the problem it actually solves is much smaller than the problem stated. It only applies to non-stationary environments where only one copy of the environment is available. If multiple copies of the environment are available, then I would wager that standard reinforcement learning techniques will far outperform this. Furthermore, reinforcement learning with only one copy of the environment (in other words, non-parallel) has proven to be inadequate for real problems because it is impossible to get enough data.