Abstract: How can we control a system without knowing beforehand what the controls do? In particular, how should we balance the imperatives to "explore" (learn what the controls do) and "exploit" (use what we've learned so far to make the system do what we want)? We won't have enough data to apply deep learning. The talk poses several toy problems and solves some of them.
Joint work with Princeton prof Clancy Rowley and grad students Bernard Guillen, Sam Otto, Amlan Sinha and Melanie Weber.
Charles Fefferman is a professor in the Math Department of Princeton University.