| Deep q-learning from demonstrations T Hester, M Vecerik, O Pietquin, M Lanctot, T Schaul, B Piot, D Horgan, ... Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 403 | 2018 |
| Leveraging demonstrations for deep reinforcement learning on robotics problems with sparse rewards M Vecerik, T Hester, J Scholz, F Wang, O Pietquin, B Piot, N Heess, ... arXiv preprint arXiv:1707.08817, 2017 | 223 | 2017 |
| A novel approach to monitor rehabilitation outcomes in stroke survivors using wearable technology S Patel, R Hughes, T Hester, J Stein, M Akay, JG Dy, P Bonato Proceedings of the IEEE 98 (3), 450-461, 2010 | 172 | 2010 |
| Learning from demonstrations for real world reinforcement learning T Hester, M Vecerik, O Pietquin, M Lanctot, T Schaul, B Piot, A Sendonaris, ... | 127 | 2017 |
| Generalized model learning for reinforcement learning on a humanoid robot T Hester, M Quinlan, P Stone 2010 IEEE International Conference on Robotics and Automation, 2369-2374, 2010 | 118 | 2010 |
| Challenges of real-world reinforcement learning G Dulac-Arnold, D Mankowitz, T Hester arXiv preprint arXiv:1904.12901, 2019 | 110 | 2019 |
| TEXPLORE: real-time sample-efficient reinforcement learning for robots T Hester, P Stone Machine learning 90 (3), 385-429, 2013 | 108 | 2013 |
| Using wearable sensors to measure motor abilities following stroke T Hester, R Hughes, DM Sherrill, B Knorr, M Akay, J Stein, P Bonato International Workshop on Wearable and Implantable Body Sensor Networks (BSN …, 2006 | 102 | 2006 |
| Safe exploration in continuous action spaces G Dalal, K Dvijotham, M Vecerik, T Hester, C Paduraru, Y Tassa arXiv preprint arXiv:1801.08757, 2018 | 83 | 2018 |
| Methods and apparatus for using smart environment devices via application program interfaces I Karp, L Stesin, C Pi-Sunyer, MA Mcbride, A Dubman, J Lyons, SW Kortz, ... US Patent App. 15/380,767, 2017 | 83 | 2017 |
| Intelligent configuration of a smart environment based on arrival time PP Reddy, M Malhotra, EJ Fisher, T Hester, MA McBride, Y Matsuoka US Patent App. 14/531,805, 2015 | 76 | 2015 |
| Learned overrides for home security MR Malhotra, S Le Guen, JA Boyd, JT Lee, T Hester US Patent 9,520,049, 2016 | 68 | 2016 |
| Generalized model learning for reinforcement learning in factored domains T Hester, P Stone Proceedings of The 8th International Conference on Autonomous Agents and …, 2009 | 68 | 2009 |
| The utility of temporal abstraction in reinforcement learning. NK Jong, T Hester, P Stone AAMAS (1), 299-306, 2008 | 68 | 2008 |
| Intrinsically motivated model learning for developing curious robots T Hester, P Stone Artificial Intelligence 247, 170-186, 2017 | 67 | 2017 |
| Analysis of the severity of dyskinesia in patients with Parkinson's disease via wearable sensors S Patel, D Sherrill, R Hughes, T Hester, N Huggins, T Lie-Nemeth, ... International Workshop on Wearable and Implantable Body Sensor Networks (BSN …, 2006 | 65 | 2006 |
| RTMBA: A real-time model-based reinforcement learning architecture for robot control T Hester, M Quinlan, P Stone 2012 IEEE International Conference on Robotics and Automation, 85-90, 2012 | 60 | 2012 |
| Tracking motor recovery in stroke survivors undergoing rehabilitation using wearable technology S Patel, R Hughes, T Hester, J Stein, M Akay, J Dy, P Bonato 2010 Annual International Conference of the IEEE Engineering in Medicine and …, 2010 | 51 | 2010 |
| Learning and using models T Hester, P Stone Reinforcement learning, 111-141, 2012 | 49 | 2012 |
| Observe and look further: Achieving consistent performance on atari T Pohlen, B Piot, T Hester, MG Azar, D Horgan, D Budden, G Barth-Maron, ... arXiv preprint arXiv:1805.11593, 2018 | 45 | 2018 |
Peter StoneProfessor of Computer Science, The University of Texas at AustinVerified email at cs.utexas.edu
