| Legibility and predictability of robot motion AD Dragan, KCT Lee, SS Srinivasa 2013 8th ACM/IEEE International Conference on Human-Robot Interaction (HRI …, 2013 | 883 | 2013 |
| CHOMP: Covariant Hamiltonian Optimization for Motion Planning M Zucker, N Ratliff, AD Dragan, M Pivtoraiko, M Klingensmith, C Dellin, ... International Journal of Robotics Research, 2013 | 849 | 2013 |
| Cooperative Inverse Reinforcement Learning D Hadfield-Menell, A Dragan, P Abbeel, S Russell Neural Information Processing Systems (NIPS), 2016 | 816 | 2016 |
| Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context G Team, P Georgiev, VI Lei, R Burnell, L Bai, A Gulati, G Tanzer, ... arXiv preprint arXiv:2403.05530, 2024 | 702 | 2024 |
| Planning for autonomous cars that leverage effects on human actions. D Sadigh, S Sastry, SA Seshia, AD Dragan Robotics: Science and systems 2, 1-9, 2016 | 632 | 2016 |
| Inverse reward design D Hadfield-Menell, S Milli, P Abbeel, SJ Russell, A Dragan Advances in neural information processing systems 30, 2017 | 487 | 2017 |
| On the utility of learning about humans for human-ai coordination M Carroll, R Shah, MK Ho, T Griffiths, S Seshia, P Abbeel, A Dragan Advances in neural information processing systems 32, 2019 | 440 | 2019 |
| A policy-blending formalism for shared control AD Dragan, SS Srinivasa The International Journal of Robotics Research 32 (7), 790-805, 2013 | 435 | 2013 |
| Active preference-based learning of reward functions D Sadigh, AD Dragan, S Sastry, S Seshia RSS, 2017 | 421 | 2017 |
| Effects of robot motion on human-robot collaboration AD Dragan, S Bauman, J Forlizzi, SS Srinivasa Proceedings of the tenth annual ACM/IEEE international conference on human …, 2015 | 406 | 2015 |
| Open problems and fundamental limitations of reinforcement learning from human feedback S Casper, X Davies, C Shi, TK Gilbert, J Scheurer, J Rando, R Freedman, ... arXiv preprint arXiv:2307.15217, 2023 | 382 | 2023 |
| On stochastic optimal control and reinforcement learning by approximate inference K Rawlik, M Toussaint, S Vijayakumar | 374 | 2013 |
| SQIL: imitation learning via regularized behavioral cloning S Reddy, AD Dragan, S Levine arXiv preprint arXiv:1905.11108 2 (5), 2019 | 351* | 2019 |
| Toward seamless human-robot handovers K Strabala, MK Lee, A Dragan, J Forlizzi, SS Srinivasa, M Cakmak, ... Journal of Human-Robot Interaction 2 (1), 112-132, 2013 | 343 | 2013 |
| Hierarchical game-theoretic planning for autonomous vehicles JF Fisac, E Bronstein, E Stefansson, D Sadigh, SS Sastry, AD Dragan 2019 International conference on robotics and automation (ICRA), 9590-9596, 2019 | 293 | 2019 |
| Dart: Noise injection for robust imitation learning M Laskey, J Lee, R Fox, A Dragan, K Goldberg Conference on robot learning, 143-156, 2017 | 273 | 2017 |
| Information gathering actions over human internal state D Sadigh, SS Sastry, SA Seshia, A Dragan 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2016 | 244 | 2016 |
| Planning for cars that coordinate with people: leveraging effects on human actions for planning and active information gathering over human internal state D Sadigh, N Landolfi, SS Sastry, SA Seshia, AD Dragan Autonomous Robots 42, 1405-1426, 2018 | 230 | 2018 |
| Generating legible motion A Dragan, S Srinivasa Carnegie Mellon University, 2013 | 221 | 2013 |
| Do you want your autonomous car to drive like you? C Basu, Q Yang, D Hungerman, M Singhal, AD Dragan Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot …, 2017 | 213 | 2017 |
Pieter AbbeelUC Berkeley | Covariant在 cs.berkeley.edu 的电子邮件经过验证
