Workshop on New Directions in Reinforcement Learning and Control

This 2-day workshop at the Institute for Advanced Study focused on research at the intersection of reinforcement learning, control and optimization. When collecting data to solve real-life and real-time problems in dynamic environments, a host of challenges arise that require novel engineering approaches and theoretical thinking at the intersection of both classical and incipient disciplines. This workshop brought together researchers working on cross-disciplinary approaches to highlight the most exciting new directions in RL and control.

The workshop was free of charge thanks to the support from the Institute for Advanced Study and the Schwab Charitable Fund made possible by the generosity of Eric and Wendy Schmidt.

Organizers:

The workshop was organized by Sanjeev Arora (IAS/Princeton University), Elad Hazan (Princeton University), Mengdi Wang (Princeton University)

Invited Speakers that confirmed:

Emma Brunskill (Stanford), Sham Kakade (U Washington), John Langford (Microsoft), Sergey Levine (Berkeley), Shie Mannor (Technion), Csaba Szepesvari (DeepMind & U Alberta), Russ Tedrake (MIT/Toyota Research Institute), Yuandong Tian (Facebook AI)

Agenda