Reinforcement Learning with Deep Energy-Based Policies H Tang, T Haarnoja, P Abbeel, S Levine arXiv preprint arXiv:1702.08165, 2017 | 490 | 2017 |
# exploration: A study of count-based exploration for deep reinforcement learning H Tang, R Houthooft, D Foote, A Stooke, OAIX Chen, Y Duan, J Schulman, ... Advances in neural information processing systems, 2753-2762, 2017 | 346 | 2017 |
Modular architecture for starcraft ii with deep reinforcement learning D Lee, H Tang, J Zhang, H Xu, T Darrell, P Abbeel Proceedings of the AAAI Conference on Artificial Intelligence and …, 2018 | 26 | 2018 |
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 | 16 | 2019 |
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 | 2 | 2018 |
Towards Informed Exploration for Deep Reinforcement Learning H Tang UC Berkeley, 2019 | | 2019 |