Safety, Risk and Uncertainty in RL

8:50 AM: Welcome and opening remarks

9:00 AM: Sergey Levine - Robust and Uncertainty-Aware Reinforcement Learning

9:45 AM: Contributed talk

Reinforcement Learning with Probabilistic Guarantees for Autonomous Driving

Maxime Bouton*, Jesper Karlsson, Alireza Nakhaei, Kikuo Fujimura, Mykel Kochenderfer and Jana Tumova

Risk-Sensitive Generative Adversarial Imitation Learning

Jonathan Lacotte, Mohammad Ghavamzadeh, Yinlam Chow* and Marco Pavone

Safe Actor-Critic

Arushi Jain*, Ayush Jain and Doina Precup

10:30 AM: Coffee break & Posters

11:00 AM: Dorsa Sadigh - Learning Humans’ Preferences: A human-centered approach for safe interactions

11:45 AM: Contributed talk

Robust Bayes-Adaptive Planning under Model Uncertainty

Apoorva Sharma*, James Harrison and Marco Pavone

12:00 PM: Lunch break

1:30 PM: Angela Schoellig - Reinforcement Learning for Robotics: Provable Safety and Performance Guarantees by Combining Models and Data

2:15 PM: Contributed talk

Contextual Policy Optimisation

Supratik Paul*, Michael Osborne and Shimon Whiteson

2:30 PM: Jamie Morgenstern

3:15 PM: Contributed talk

A Fitted-Q Algorithm for Budgeted MDPs

Nicolas Carrara*, Romain Laroche, Tanguy Urvoy, Olivier Pietquin and Jean Leon Bouraoui

3:30 PM: Coffee break & Posters

4:00 PM: Philip Thomas - A New Type of Safe Reinforcement Learning

4:45 PM: Contributed talks

Safe Policy Improvement with Baseline Bootstrapping

Romain Laroche and Paul Trichelair*

Soft Safe Policy Improvement with Baseline Bootstrapping

Kimia Nadjahi, Romain Laroche, Rémi Tachet des Combes and Paul Trichelair*

5:15 PM: Closing remarks

5:25 PM: Poster session