| Interactive learning from policy-dependent human feedback J MacGlashan, MK Ho, R Loftin, B Peng, G Wang, DL Roberts, ME Taylor, ... Proceedings of the 34th International Conference on Machine Learning-Volume …, 2017 | 45 | 2017 |
| A strategy-aware technique for learning behaviors from discrete human feedback RT Loftin, J MacGlashan, B Peng, ME Taylor, ML Littman, J Huang, ... Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014 | 44 | 2014 |
| Learning behaviors via human-delivered discrete feedback: modeling implicit feedback strategies to speed up learning R Loftin, B Peng, J MacGlashan, ML Littman, ME Taylor, J Huang, ... Autonomous agents and multi-agent systems 30 (1), 30-59, 2016 | 42 | 2016 |
| Reinforcement learning as a framework for ethical decision making D Abel, J MacGlashan, ML Littman Workshops at the Thirtieth AAAI Conference on Artificial Intelligence, 2016 | 38 | 2016 |
| Interactive visual clustering M Desjardins, J MacGlashan, J Ferraioli Proceedings of the 12th international conference on Intelligent user …, 2007 | 33 | 2007 |
| A need for speed: Adapting agent action speed to improve task learning from non-expert humans B Peng, J MacGlashan, R Loftin, ML Littman, DL Roberts, ME Taylor Proceedings of the 2016 International Conference on Autonomous Agents …, 2016 | 31 | 2016 |
| Showing versus doing: Teaching by demonstration MK Ho, M Littman, J MacGlashan, F Cushman, JL Austerweil Advances in neural information processing systems, 3027-3035, 2016 | 29 | 2016 |
| Goal-based action priors D Abel, DE Hershkowitz, G Barth-Maron, S Brawner, K O'Farrell, ... Twenty-Fifth International Conference on Automated Planning and Scheduling, 2015 | 28 | 2015 |
| Environment-independent task specifications via gltl ML Littman, U Topcu, J Fu, C Isbell, M Wen, J MacGlashan arXiv preprint arXiv:1704.04341, 2017 | 27 | 2017 |
| Grounding English Commands to Reward Functions. J MacGlashan, M Babes-Vroman, Marie desJardins, ML Littman, ... Robotics: Science and Systems, 2015 | 22 | 2015 |
| Reducing errors in object-fetching interactions through social feedback D Whitney, E Rosen, J MacGlashan, LLS Wong, S Tellex 2017 IEEE International Conference on Robotics and Automation (ICRA), 1006-1013, 2017 | 20 | 2017 |
| Between imitation and intention learning J MacGlashan, ML Littman Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015 | 20 | 2015 |
| Social is special: A normative framework for teaching with and learning from evaluative feedback MK Ho, J MacGlashan, ML Littman, F Cushman Cognition 167, 91-106, 2017 | 19 | 2017 |
| Portable option discovery for automated learning transfer in object-oriented Markov decision processes N Topin, N Haltmeyer, S Squire, J Winder, J MacGlashan Twenty-Fourth International Joint Conference on Artificial Intelligence, 2015 | 18 | 2015 |
| Brown-umbc reinforcement learning and planning (burlap) J MacGlashan | 16 | 2015 |
| Minecraft as an experimental world for ai in robotics KC Aluru, S Tellex, J Oberlin, J MacGlashan 2015 AAAI Fall Symposium Series, 2015 | 15 | 2015 |
| Learning something from nothing: Leveraging implicit human feedback strategies R Loftin, B Peng, J MacGlashan, ML Littman, ME Taylor, J Huang, ... The 23rd IEEE International Symposium on Robot and Human Interactive …, 2014 | 15 | 2014 |
| Training an agent to ground commands with reward and punishment J MacGlashan, M Littman, R Loftin, B Peng, D Roberts, M Taylor Workshops at the Twenty-Eighth AAAI Conference on Artificial Intelligence, 2014 | 15 | 2014 |
| Marie desJardins, Michael L. Littman, Smaranda Muresan, Shawn Squire, Stefanie Tellex, Dilip Arumugam, and Lei Yang. Grounding english commands to reward functions J MacGlashan, M Babes-Vroman Robotics: Science and Systems, 2015 | 13 | 2015 |
| Planning with abstract Markov decision processes N Gopalan, ML Littman, J MacGlashan, S Squire, S Tellex, J Winder, ... Twenty-Seventh International Conference on Automated Planning and Scheduling, 2017 | 12 | 2017 |
