- Variational Inverse Control with Events: A General Framework for Data-Driven Reward Definition. Avi Singh, Justin Fu, Dibya Ghosh, Larry Yang and Sergey Levine
- DeepMimic: Example-Guided Deep Reinforcement Learning of Physics-Based Character Skills. Xue Bin Peng, Pieter Abbeel, Sergey Levine and Michiel van de Panne.
- Challenging the MDP Status Quo: An Axiomatic Approach to Rationality for Reinforcement Learning Agents. Silviu Pitis
- Recurrent Existence Determination Through Policy Optimization. Baoxiang Wang
- Multi-Task Maximum Causal Entropy Inverse Reinforcement Learning. Adam Gleave and Oliver Habryka
- Designing a Multi-Objective Reward Function for Creating Teams of Robotic Bodyguards Using Deep Reinforcement Learning. Hassam Sheikh and Ladisalu Boloni
- Using Reward Machines for High-Level Task Specification and Decomposition in Reinforcement Learning. Rodrigo Toro Icarte, Toryn Q. Klassen, Richard Valenzano and Sheila A. McIlraith
- Augmenting Experience via Teachers' Advice. Yuhuai Wu, Harris Chan, Sanja Fidler and Jimmy Ba
- Diversity is All You Need: Learning Skills without a Reward Function. Benjamin Eysenbach, Abhishek Gupta, Julian Ibarz and Sergey Levine
- Exploring Hierarchy-Aware Inverse Reinforcement Learning. Chris Cundy and Daniel Filan
- Learning a Prior over Intent via Meta-Inverse Reinforcement Learning. Kelvin Xu, Ellis Ratner, Anca Dragan, Sergey Levine and Chelsea Finn
- Unsupervised Meta-Learning for Reinforcement Learning. Abhishek Gupta, Benjamin Eysenbach, Chelsea Finn and Sergey Levine
- Multi-Agent Generative Adversarial Imitation Learning. Jiaming Song, Hongyu Ren, Dorsa Sadigh and Stefano Ermon.
- Visual Reinforcement Learning with Imagined Goals. Ashvin Nair, Vitchyr Pong, Murtaza Dalal, Shikhar Bahl, Steven Lin and Sergey Levine
- SILC : Smoother Imitation with Lipschitz Costs. Sapana Chaudhary, Akshat Dave and Balaraman Ravindran
- Active Inverse Reward Design. Sören Mindermann, Rohin Shah, Adam Gleave and Dylan Hadfield-Menell
- Non-Markovian Rewards Expressed in LTL: Guiding Search Via Reward Shaping (Extended Version). Alberto Camacho, Oscar Chen, Scott Sanner and Sheila McIlraith
- Few-Shot Goal Inference for Visuomotor Learning and Planning. Annie Xie, Avi Singh, Sergey Levine and Chelsea Finn