Haoran Tang
Haoran Tang
PhD student in Applied Mathematics; University of California, Berkeley
Verified email at - Homepage
Cited by
Cited by
Reinforcement Learning with Deep Energy-Based Policies
H Tang, T Haarnoja, P Abbeel, S Levine
arXiv preprint arXiv:1702.08165, 2017
# exploration: A study of count-based exploration for deep reinforcement learning
H Tang, R Houthooft, D Foote, A Stooke, OAI Xi Chen, Y Duan, ...
Advances in neural information processing systems 30, 2017
Why does hierarchy (sometimes) work so well in reinforcement learning?
O Nachum, H Tang, X Lu, S Gu, H Lee, S Levine
arXiv preprint arXiv:1909.10618, 2019
Modular architecture for starcraft ii with deep reinforcement learning
D Lee, H Tang, JO Zhang, H Xu, T Darrell, P Abbeel
Fourteenth Artificial Intelligence and Interactive Digital Entertainment …, 2018
Systems and methods for robotic picking
Y Duan, X Chen, M Rohaninejad, N Mishra, YX Liu, AA Vaziri, T Haoran, ...
US Patent App. 17/014,545, 2021
Hierarchical deep reinforcement learning agent with counter self-play on competitive games
H Xu, K Paster, Q Chen, H Tang, P Abbeel, T Darrell, S Levine
Towards Informed Exploration for Deep Reinforcement Learning
H Tang
University of California, Berkeley, 2019
Trajectory optimization using neural networks
T Haoran, X Chen, Y Duan, N Mishra, S Wu, M Sieb, Y Shentu
US Patent App. 17/193,870, 2021
Training artificial networks for robotic picking
Y Duan, T Haoran, Y Shentu, N Mishra, X Chen
US Patent App. 17/014,558, 2021
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