Adding a bit of internet research from this morning, hopefully it helps. Of course, AIs are not a magic wand and we should not expect this. Deep reinforcement l

Adding a bit of internet research from this morning, hopefully it helps. Of course, AIs are not a magic wand and we should not expect this. Deep reinforcement learning for stochastic dynamic systems is still extremely difficult, most of all it is the Markov chains modeling / unmodeling to make scenarios ultimately unreliable. Running a number of these scenarios to achieve the statistical grade maybe? Weather forecasting seems a viable analogy and a first order approximation, at this time, even if time-series predictions are passive while rl agents interact and optimize (that's why climate change with human's effect, agents playing humans or any other stakeholder). We will see.