I am looking for collaborators to apply RL in real-world applications. I am excited about RL for X, with X being power grid, network control, personalized recommendations, robotics, education, etc. Note that I am looking for RL for real X, not RL for simulation of X; see this thread for more details. Long story short: if you have the platform for deploying new decision-making strategies and doing A/B testing with real users/customers/patients/students/etc, I am all ears!
An intermediate ground between “RL for X” and “RL for simulator of X” is a setting I call “supervised-learning generalization, RL optimization”. They have real-world impact, but I am only interested if the project inspires methodology innovations. Examples include:
The commonality of all above examples is that it is relatively easy to do counterfactual reasoning with the data available (“had I done something different that day, what would happen”), effectively creating a simulator. There are still statistical challenges to generalize to new scenarios (new stock, new job request patterns, new demand, etc), but that is wrt a fixed distribution and does not involve distribution shift due to decision making, a central challenge in statistical RL.
As mentioned above, I have moderate interest in such scenarios. On the other hand, if you have a problem where such counterfactual reasoning is hard and not obvious (what we call “off-policy evaluation”), and you are convinced that it’s an RL problem where long-term consequences need to be accounted for seriously, I will be very excited to discuss potential collaborations!