| Reward design with language models M Kwon, SM Xie, K Bullard, D Sadigh arXiv preprint arXiv:2303.00001, 2023 | 157 | 2023 |
| Active learning within constrained environments through imitation of an expert questioner K Bullard, Y Schroecker, S Chernova arXiv preprint arXiv:1907.00921, 2019 | 22 | 2019 |
| Human-driven feature selection for a robotic agent learning classification tasks from demonstration K Bullard, S Chernova, AL Thomaz 2018 IEEE International Conference on Robotics and Automation (ICRA), 6923-6930, 2018 | 21 | 2018 |
| Towards intelligent arbitration of diverse active learning queries K Bullard, AL Thomaz, S Chernova 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2018 | 19 | 2018 |
| Multimodal real-time contingency detection for HRI V Chu, K Bullard, AL Thomaz 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2014 | 18 | 2014 |
| Grounding action parameters from demonstration K Bullard, B Akgun, S Chernova, AL Thomaz 2016 25th IEEE International Symposium on Robot and Human Interactive …, 2016 | 17 | 2016 |
| Situated Mapping for Transfer Learning T Fitzgerald, K Bullard, AL Thomaz, A Goel Fourth Annual Conference on Advances in Cognitive Systems, 2016 | 15 | 2016 |
| Exploring zero-shot emergent communication in embodied multi-agent populations K Bullard, F Meier, D Kiela, J Pineau, J Foerster arXiv preprint arXiv:2010.15896, 2020 | 14 | 2020 |
| Quasi-equivalence discovery for zero-shot emergent communication K Bullard, D Kiela, F Meier, J Pineau, J Foerster arXiv preprint arXiv:2103.08067, 2021 | 13 | 2021 |
| Auto-aligning multiagent incentives with global objectives M Kwon, JP Agapiou, EA Duéñez-Guzmán, R Elie, G Piliouras, K Bullard, ... ICML Workshop on Localized Learning (LLW), 2023 | 5 | 2023 |
| Development of a genetic fuzzy controller for an unmanned aerial vehicle Y Qu, S Pandhiti, KS Bullard, WD Potter, KF Fezer International Conference on Industrial, Engineering and Other Applications …, 2011 | 5 | 2011 |
| Developing, evaluating and scaling learning agents in multi-agent environments I Gemp, T Anthony, Y Bachrach, A Bhoopchand, K Bullard, J Connor, ... AI Communications 35 (4), 271-284, 2022 | 4 | 2022 |
| An HRI Approach to Learning from Demonstration B Akgun, K Bullard, V Chu, AL Thomaz 2014 AAAI Fall Symposium Series, 2014 | 3 | 2014 |
| Approximating the Core via Iterative Coalition Sampling I Gemp, M Lanctot, L Marris, Y Mao, E Duéñez-Guzmán, S Perrin, ... arXiv preprint arXiv:2402.03928, 2024 | 1 | 2024 |
| THEORETICAL PRINCIPLES OF MULTI-AGENT REIN-FORCEMENT LEARNING FOR COALITIONAL BARGAIN-ING GAMES L Cipolina-Kun, I Carlucho, S Mak, K Bullard, V Yazdanpanah, E Gerding, ... International Conference on Learning Representations, 2023 | | 2023 |
| MULTI-AGENT REINFORCEMENT LEARNING FOR COALITIONAL BARGAINING GAMES L Cipolina-Kun, S Mak, I Carlucho, V Yazdanpanah, S Stein, E Gerding, ... | | 2023 |
| Managing learning interactions for collaborative robot learning K Bullard Georgia Institute of Technology, 2019 | | 2019 |
| Proceedings of the AI-HRI Symposium at AAAI-FSS 2018 K Bullard, N DePalma, RG Freedman, B Hayes, L Iocchi, K Lohan, ... arXiv preprint arXiv:1809.06606, 2018 | | 2018 |
| An HRI Approach to Feature Selection K Bullard, S Chernova, AL Thomaz 2016 AAAI Fall Symposium Series, 2016 | | 2016 |
| Embodied Queries for Robot Task Learning K Bullard Workshop at The Eleventh ACM/IEEE International Conference on Human Robot …, 2016 | | 2016 |
Andrea ThomazInteractive Computing, Georgia Institute of TechnologyVerified email at ece.utexas.edu
