| Apprenticeship learning via inverse reinforcement learning P Abbeel, AY Ng Proceedings of the twenty-first international conference on Machine learning, 1, 2004 | 1938 | 2004 |
| Trust region policy optimization J Schulman, S Levine, P Abbeel, M Jordan, P Moritz International conference on machine learning, 1889-1897, 2015 | 1703 | 2015 |
| Introduction to statistical relational learning D Koller, N Friedman, S Džeroski, C Sutton, A McCallum, A Pfeffer, ... MIT press, 2007 | 1536 | 2007 |
| Infogan: Interpretable representation learning by information maximizing generative adversarial nets X Chen, Y Duan, R Houthooft, J Schulman, I Sutskever, P Abbeel Advances in neural information processing systems, 2172-2180, 2016 | 1465 | 2016 |
| End-to-end training of deep visuomotor policies S Levine, C Finn, T Darrell, P Abbeel The Journal of Machine Learning Research 17 (1), 1334-1373, 2016 | 1455 | 2016 |
| Model-agnostic meta-learning for fast adaptation of deep networks C Finn, P Abbeel, S Levine Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 1069 | 2017 |
| Discriminative probabilistic models for relational data B Taskar, P Abbeel, D Koller Proceedings of the Eighteenth conference on Uncertainty in artificial …, 2002 | 839 | 2002 |
| Benchmarking deep reinforcement learning for continuous control Y Duan, X Chen, R Houthooft, J Schulman, P Abbeel International Conference on Machine Learning, 1329-1338, 2016 | 649 | 2016 |
| High-dimensional continuous control using generalized advantage estimation J Schulman, P Moritz, S Levine, M Jordan, P Abbeel arXiv preprint arXiv:1506.02438, 2015 | 637 | 2015 |
| An application of reinforcement learning to aerobatic helicopter flight P Abbeel, A Coates, M Quigley, AY Ng Advances in neural information processing systems, 1-8, 2007 | 583 | 2007 |
| Link prediction in relational data B Taskar, MF Wong, P Abbeel, D Koller Advances in neural information processing systems, 659-666, 2004 | 527 | 2004 |
| A survey of research on cloud robotics and automation B Kehoe, S Patil, P Abbeel, K Goldberg IEEE Transactions on automation science and engineering 12 (2), 398-409, 2015 | 513 | 2015 |
| Domain randomization for transferring deep neural networks from simulation to the real world J Tobin, R Fong, A Ray, J Schneider, W Zaremba, P Abbeel 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2017 | 454 | 2017 |
| Multi-agent actor-critic for mixed cooperative-competitive environments R Lowe, Y Wu, A Tamar, J Harb, OAIP Abbeel, I Mordatch Advances in Neural Information Processing Systems, 6379-6390, 2017 | 450 | 2017 |
| Autonomous helicopter aerobatics through apprenticeship learning P Abbeel, A Coates, AY Ng The International Journal of Robotics Research 29 (13), 1608-1639, 2010 | 446 | 2010 |
| Hindsight experience replay M Andrychowicz, F Wolski, A Ray, J Schneider, R Fong, P Welinder, ... Advances in Neural Information Processing Systems, 5048-5058, 2017 | 387 | 2017 |
| Efficient l~ 1 regularized logistic regression SI Lee, H Lee, P Abbeel, AY Ng AAAI 6, 401-408, 2006 | 382 | 2006 |
| LQG-MP: Optimized path planning for robots with motion uncertainty and imperfect state information J Van Den Berg, P Abbeel, K Goldberg The International Journal of Robotics Research 30 (7), 895-913, 2011 | 368 | 2011 |
| Soft actor-critic: Off-policy maximum entropy deep reinforcement learning with a stochastic actor T Haarnoja, A Zhou, P Abbeel, S Levine arXiv preprint arXiv:1801.01290, 2018 | 329 | 2018 |
| Cloth grasp point detection based on multiple-view geometric cues with application to robotic towel folding J Maitin-Shepard, M Cusumano-Towner, J Lei, P Abbeel 2010 IEEE International Conference on Robotics and Automation, 2308-2315, 2010 | 325 | 2010 |
Sergey LevineUC Berkeley, GoogleVerified email at eecs.berkeley.edu
