Hankz Hankui Zhuo
Hankz Hankui Zhuo
Faculty@School of Data and Computer Science, Sun Yat-sen University
Verified email at mail.sysu.edu.cn - Homepage
Cited by
Cited by
Plan, activity, and intent recognition: Theory and practice
G Sukthankar, C Geib, HH Bui, D Pynadath, RP Goldman
Newnes, 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
Learning complex action models with quantifiers and logical implications
HH Zhuo, Q Yang, DH Hu, L Li
Artificial Intelligence 174 (18), 1540-1569, 2010
Action-model acquisition from noisy plan traces
HH Zhuo, S Kambhampati
Twenty-Third International Joint Conference on Artificial Intelligence, 2013
Refining incomplete planning domain models through plan traces
HH Zhuo, T Nguyen, S Kambhampati
Twenty-third international joint conference on artificial intelligence, 2013
Action-model acquisition for planning via transfer learning
HH Zhuo, Q Yang
Artificial intelligence 212, 80-103, 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
Learning hierarchical task network domains from partially observed plan traces
HH Zhuo, H Muñoz-Avila, Q Yang
Artificial intelligence 212, 134-157, 2014
Federated reinforcement learning
HH Zhuo, W Feng, Q Xu, Q Yang, Y Lin
Action-model based multi-agent plan recognition
H Zhuo, Q Yang, S Kambhampati
Advances in Neural Information Processing Systems 25 1, 368, 2012
Extracting action sequences from texts based on deep reinforcement learning
W Feng, HH Zhuo, S Kambhampati
IJCAI, 2018
Multi-agent plan recognition with partial team traces and plan libraries
HH Zhuo, L Li
Twenty-Second International Joint Conference on Artificial Intelligence, 2011
Crowdsourced action-model acquisition for planning
H Zhuo
Proceedings of the AAAI Conference on Artificial Intelligence 29 (1), 2015
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
Transferring knowledge from another domain for learning action models
H Zhuo, Q Yang, D Hu, L Li
PRICAI 2008: Trends in Artificial Intelligence, 1110-1115, 2008
Model-lite planning: Case-based vs. model-based approaches
HH Zhuo, S Kambhampati
Artificial Intelligence 246, 1-21, 2017
Abnormal activity detection using pyroelectric infrared sensors
X Luo, H Tan, Q Guan, T Liu, HH Zhuo, B Shen
Sensors 16 (6), 822, 2016
Plan explicability for robot task planning
Y Zhang, S Sreedharan, A Kulkarni, T Chakraborti, HH Zhuo, ...
Proceedings of the RSS Workshop on Planning for Human-Robot Interaction …, 2016
Discovering underlying plans based on distributed representations of actions
X Tian, HH Zhuo, S Kambhampati
arXiv preprint arXiv:1511.05662, 2015
Model-Lite Case-Based Planning
HH Zhuo, T Nguyen, S Kambhampati
AAAI-13, 1077-1083, 2013
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