| Tactics of adversarial attack on deep reinforcement learning agents YC Lin, ZW Hong, YH Liao, ML Shih, MY Liu, M Sun Proceedings of the 26th International Joint Conference on Artificial …, 2017 | 293 | 2017 |
| A deep policy inference q-network for multi-agent systems ZW Hong, SY Su, TY Shann, YH Chang, CY Lee arXiv preprint arXiv:1712.07893, 2017 | 75 | 2017 |
| Diversity-Driven Exploration Strategy for Deep Reinforcement Learning ZW Hong, TY Shann, SY Su, YH Chang, CY Lee Proceedings of the 32nd Conference on Neural Information Processing Systems, 2018 | 64 | 2018 |
| Virtual-to-Real: Learning to Control in Visual Semantic Segmentation ZW Hong, C Yu-Ming, SY Su, TY Shann, YH Chang, HK Yang, BHL Ho, ... Proceedings of the 27th International Joint Conference on Artificial …, 2018 | 63 | 2018 |
| Model-based lookahead reinforcement learning ZW Hong, J Pajarinen, J Peters arXiv preprint arXiv:1908.06012, 2019 | 8 | 2019 |
| Periodic Intra-ensemble Knowledge Distillation for Reinforcement Learning ZW Hong, P Nagarajan, G Maeda Joint European Conference on Machine Learning and Knowledge Discovery in …, 2021 | 2 | 2021 |
| Adversarial Active Exploration for Inverse Dynamics Model Learning ZW Hong, TJ Fu, TY Shann, YH Chang, CY Lee Proceedings of the 3rd Conference on Robot Learning, 2019 | 2 | 2019 |
| Bilinear value networks ZW Hong, G Yang, P Agrawal arXiv preprint arXiv:2204.13695, 2022 | 1 | 2022 |
| Topological Experience Replay ZW Hong, T Chen, YC Lin, J Pajarinen, P Agrawal arXiv preprint arXiv:2203.15845, 2022 | 1 | 2022 |
| Collaborative Inter-agent Knowledge Distillation for Reinforcement Learning ZW Hong, P Nagarajan, G Maeda | 1 | 2019 |
| Stubborn: A Strong Baseline for Indoor Object Navigation H Luo, A Yue, ZW Hong, P Agrawal arXiv preprint arXiv:2203.07359, 2022 | | 2022 |
| Bi-linear Value Networks for Multi-goal Reinforcement Learning ZW Hong, G Yang, P Agrawal International Conference on Learning Representations, 2021 | | 2021 |
| Reducing the Deployment-Time Inference Control Costs of Deep Reinforcement Learning Agents via an Asymmetric Architecture CJ Chang, YW Chu, CH Ting, HK Liu, ZW Hong, CY Lee 2021 IEEE International Conference on Robotics and Automation (ICRA), 4762-4768, 2021 | | 2021 |
| Topological Experience Replay for Fast Q-Learning ZW Hong, T Chen, YC Lin, J Pajarinen, P Agrawal | | 2021 |
| Mixture of Step Returns in Bootstrapped DQN PH Chiang, HK Yang, ZW Hong, CY Lee arXiv preprint arXiv:2007.08229, 2020 | | 2020 |
| Toward Synergism in Macro Action Ensembles YM Chen, KY Chang, C Liu, TC Hsiao, ZW Hong, CY Lee | | 2020 |
| A Self-Supervised Method for Mapping Human Instructions to Robot Policies HW Yu, PY Wu, CA Tsao, YA Shen, SH Lin, ZW Hong, YH Chang, CY Lee | | 2018 |
| A Deep Policy Inference Q-Network for Multi-Agent Systems Download PDF ZW Hong, SY Su, TY Shann, YH Chang, CY Lee | | |
| Swarm-inspired Reinforcement Learning via Collaborative Inter-agent Knowledge Distillation ZW Hong, P Nagarajan, G Maeda | | |
| Sim-to-Real: Autonomous Robotic Control ZW Hong, YM Chen, H Yang, HW Hsiao, SP Lai | | |
Chun-Yi LeeDepartment of Computer Science, National Tsing Hua UniversityEmail verificata su cs.nthu.edu.tw
