Awards

• SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous Driving by Ming Zhou et al.

• DIRL: Domain-Invariant Representation Learning for Sim-to-Real Transfer by Ajay Tanwani

🏆 Winner: SMARTS: An Open-Source Scalable Multi-Agent RL Training School for Autonomous Driving by Ming Zhou (Shanghai Jiao Tong University) et al.

• Learning Latent Representations to Influence Multi-Agent Interaction by Annie Xie et al.

• Guaranteeing Safety of Learned Perception Modules via Measurement-Robust Control Barrier Functions by Sarah Dean et al.

• Learning from Suboptimal Demonstration via Self-Supervised Reward Regression by Letian Chen et al.

• Safe Optimal Control Using Stochastic Barrier Functions and Deep Forward-Backward SDEs by Marcus A Pereira et al.

🏆 Winner: Learning Latent Representations to Influence Multi-Agent Interaction by Annie Xie (Stanford University)*; Dylan Losey (Stanford University); Ryan Tolsma (Stanford University); Chelsea Finn (Stanford); Dorsa Sadigh (Stanford)

• Universal Embeddings for Spatio-Temporal Tagging of Self-Driving Logs presented by Sean Segal (Uber ATG)

• Transporter Networks: Rearranging the Visual World for Robotic Manipulation presented by Andy Zeng (Google)

• Accelerating Reinforcement Learning with Learned Skill Priors presented by Karl Pertsch (University of Southern California)

🏆 Winner: Accelerating Reinforcement Learning with Learned Skill Priors presented by Karl Pertsch (University of Southern California)