| Plan, activity, and intent recognition: Theory and practice G Sukthankar, C Geib, HH Bui, D Pynadath, RP Goldman Newnes, 2014 | 313 | 2014 |
| Plan explicability and predictability for robot task planning Y Zhang, S Sreedharan, A Kulkarni, T Chakraborti, HH Zhuo, ... 2017 IEEE international conference on robotics and automation (ICRA), 1313-1320, 2017 | 213 | 2017 |
| Federated deep reinforcement learning HH Zhuo, W Feng, Y Lin, Q Xu, Q Yang arXiv preprint arXiv:1901.08277, 2019 | 197 | 2019 |
| Learning complex action models with quantifiers and logical implications HH Zhuo, Q Yang, DH Hu, L Li Artificial Intelligence 174 (18), 1540-1569, 2010 | 166 | 2010 |
| Action-model acquisition from noisy plan traces HH Zhuo, S Kambhampati Twenty-Third International Joint Conference on Artificial Intelligence, 2013 | 115 | 2013 |
| Learning hierarchical task network domains from partially observed plan traces HH Zhuo, H Munoz-Avila, Q Yang Artificial intelligence 212, 134-157, 2014 | 88 | 2014 |
| Refining Incomplete Planning Domain Models Through Plan Traces. HH Zhuo, TA Nguyen, S Kambhampati IJCAI, 2451-2458, 2013 | 82 | 2013 |
| Action-model acquisition for planning via transfer learning HH Zhuo, Q Yang Artificial intelligence 212, 80-103, 2014 | 81 | 2014 |
| Learning HTN method preconditions and action models from partial observations HH Zhuo, DH Hu, C Hogg, Q Yang, H Munoz-Avila Twenty-First International Joint Conference on Artificial Intelligence, 2009 | 76 | 2009 |
| Extracting action sequences from texts based on deep reinforcement learning W Feng, HH Zhuo, S Kambhampati IJCAI, 2018 | 57 | 2018 |
| Combining deep learning and topic modeling for review understanding in context-aware recommendation M Jin, X Luo, H Zhu, HH Zhuo Proceedings of the 2018 Conference of the North American Chapter of the …, 2018 | 52 | 2018 |
| Coordinated proximal policy optimization Z Wu, C Yu, D Ye, J Zhang, HH Zhuo Advances in Neural Information Processing Systems 34, 26437-26448, 2021 | 48 | 2021 |
| Model-lite planning: Case-based vs. model-based approaches HH Zhuo, S Kambhampati Artificial Intelligence 246, 1-21, 2017 | 48 | 2017 |
| Creativity of ai: Automatic symbolic option discovery for facilitating deep reinforcement learning M Jin, Z Ma, K Jin, HH Zhuo, C Chen, C Yu Proceedings of the AAAI Conference on Artificial Intelligence 36 (6), 7042-7050, 2022 | 47 | 2022 |
| Multi-matching network for multiple choice reading comprehension M Tang, J Cai, HH Zhuo Proceedings of the AAAI Conference on Artificial Intelligence 33 (01), 7088-7095, 2019 | 45 | 2019 |
| Action-model based multi-agent plan recognition H Zhuo, Q Yang, S Kambhampati Advances in Neural Information Processing Systems 25, 2012 | 44 | 2012 |
| Abnormal activity detection using pyroelectric infrared sensors X Luo, H Tan, Q Guan, T Liu, HH Zhuo, B Shen Sensors 16 (6), 822, 2016 | 41 | 2016 |
| Crowdsourced action-model acquisition for planning H Zhuo Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015 | 40 | 2015 |
| Paper2vec: Citation-context based document distributed representation for scholar recommendation H Tian, HH Zhuo arXiv preprint arXiv:1703.06587, 2017 | 35 | 2017 |
| Multi-agent plan recognition with partial team traces and plan libraries HH Zhuo, L Li IJCAI 22 (1), 484, 2011 | 34 | 2011 |
Subbarao KambhampatiArizona State UniversityDirección de correo verificada de asu.edu