| Safe reinforcement learning via shielding M Alshiekh, R Bloem, R Ehlers, B Könighofer, S Niekum, U Topcu Proceedings of the AAAI conference on artificial intelligence 32 (1), 2018 | 770 | 2018 |
| Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations D Brown, W Goo, P Nagarajan, S Niekum International Conference on Machine Learning, 2019 | 378 | 2019 |
| A review of robot learning for manipulation: Challenges, representations, and algorithms O Kroemer, S Niekum, G Konidaris Journal of machine learning research 22 (30), 1-82, 2021 | 356 | 2021 |
| Learning grounded finite-state representations from unstructured demonstrations S Niekum, S Osentoski, G Konidaris, S Chitta, B Marthi, AG Barto The International Journal of Robotics Research 34 (2), 131-157, 2015 | 252 | 2015 |
| Learning and Generalization of Complex Tasks from Unstructured Demonstrations S Niekum, S Osentoski, G Konidaris, AG Barto IEEE/RSJ International Conference on Intelligent Robots and Systems, 5239-5246, 2012 | 238 | 2012 |
| Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations D Brown, W Goo, S Niekum Conference on Robot Learning, 2019 | 201 | 2019 |
| Using Natural Language for Reward Shaping in Reinforcement Learning P Goyal, S Niekum, R Mooney International Joint Conference on Artificial Intelligence, 2019 | 167 | 2019 |
| Incremental Semantically Grounded Learning from Demonstration S Niekum, S Chitta, B Marthi, S Osentoski, AG Barto Robotics: Science and Systems 2013, 2013 | 154 | 2013 |
| Safe imitation learning via fast bayesian reward inference from preferences D Brown, R Coleman, R Srinivasan, S Niekum International Conference on Machine Learning, 1165-1177, 2020 | 140* | 2020 |
| Active articulation model estimation through interactive perception K Hausman, S Niekum, S Osentoski, GS Sukhatme 2015 IEEE International Conference on Robotics and Automation (ICRA), 3305-3312, 2015 | 99 | 2015 |
| Active reward learning from critiques Y Cui, S Niekum 2018 IEEE international conference on robotics and automation (ICRA), 6907-6914, 2018 | 97 | 2018 |
| Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications D Brown, S Niekum AAAI Conference on Artificial Intelligence, 2019 | 96 | 2019 |
| Bootstrapping with models: Confidence intervals for off-policy evaluation J Hanna, P Stone, S Niekum Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017 | 84 | 2017 |
| Genetic programming for reward function search S Niekum, AG Barto, L Spector IEEE Transactions on Autonomous Mental Development 2 (2), 83-90, 2010 | 83* | 2010 |
| Risk-Aware Active Inverse Reinforcement Learning D Brown, Y Cui, S Niekum Conference on Robot Learning, 2018 | 74 | 2018 |
| Importance Sampling Policy Evaluation with an Estimated Behavior Policy J Hanna, S Niekum, P Stone International Conference on Machine Learning, 2019 | 72 | 2019 |
| Screwnet: Category-independent articulation model estimation from depth images using screw theory A Jain, R Lioutikov, C Chuck, S Niekum 2021 IEEE International Conference on Robotics and Automation (ICRA), 13670 …, 2021 | 71 | 2021 |
| Automatic detection and classification of geological features of interest DR Thompson, S Niekum, T Smith, D Wettergreen Proceedings of the IEEE Aerospace Conference, 2005 | 71* | 2005 |
| Can foundation models perform zero-shot task specification for robot manipulation? Y Cui, S Niekum, A Gupta, V Kumar, A Rajeswaran Learning for dynamics and control conference, 893-905, 2022 | 66 | 2022 |
| Human gaze assisted artificial intelligence: A review R Zhang, A Saran, B Liu, Y Zhu, S Guo, S Niekum, D Ballard, M Hayhoe IJCAI: Proceedings of the Conference 2020, 4951, 2020 | 64 | 2020 |
Daniel S. BrownAssistant Professor, Robotics Center and School of Computing, University of Utah在 cs.utah.edu 的电子邮件经过验证
